Lambda

Lambda is an asymmetrical measure of association appropriate for cross tabulations of nominal variables.


Gamma

Gamma is a measure of association to be used with ordinal or ratio variables, taking only the number of untied order pairs into account.


Dyx, Dxy

Dyx and Dxy are asymmetric measures of association that take order ties into account.  If the row variable is the dependent variable, Dyx should be used.  If the column variable is the dependent variable, then Dxy should be used. Order ties are pairs of cases with the same score on the dependent variable but different scores on the independent variable.


Tau-b and Tau-C

Tau-b and Tau-c are nonparametric measures of association for use with ordinal or ratio variables.  Tau-b takes order ties into account, while Tau-c ignores all order ties.  Order ties are pairs of cases with the same score on the dependent variable but different scores on the independent variable, or vice versa.


Standard Error

The standard error is the standard deviation of a sampling distribution.


Cramer's V

Cramer’s V is a measure of association for a table based on the value of Chi-square and it may be used with nominal variables.


Pearson's Contingency Coefficient (C)

Pearson’s Contingency Coefficient, or C, is a chi-square based, symmetric measure of association for nominal variables.


Row Variable Categories

The categories of the row variable will appear here.  In the displayed example, the row variable is POL. PARTY, which has three categories—Democrat, Independ., and Republican.  The colored box next to each category show its color in the stacked bars.


Stacked Bars

A stacked bar will appear for each category of your column variable.  In the displayed example there are two bars—one for each category of SEX.  The bars provide you with a visual display of the relative percentages of each level of the row variable within each level of the column variable.


Column Variable Categories

The categories of the column variable will appear here.  In the displayed example, the column variable is SEX, which has two categories—Male and Female.


Control Variables

The names of the control variables you selected and the levels of the control variables used in the current table will appear here.   In the displayed example there is one control variable, R.FUND/LIB.  The table shows the crosstabs for POL. PARTY by SEX for only those cases which have the value “Fundament.” (fundamentalist) on the R.FUND/LIB variable.


Control Variable Levels

This area will show the level of the control variable in the current table and the total number of tables available.   In the displayed example, the user is viewing table 1 of 5.  Use the arrows to cycle through the different tables available.


Highlighted Columns

These three columns, labeled "NORTHEAST," "N.CENTRAL," and "SOUTH" will be collapsed.  When you select a category label, its row or column will be highlighted in green (rows) or blue (columns).  To select a category label, click on its name.  In the displayed example, the user clicked on “NORTHEAST.” "N.CENTRAL," and “SOUTH.”


Variable Names

The names of your variables will appear here in the following format: ROW by COLUMN.  In the current example, REL.IMP? is the row variable and REGION the column variable.


Name of New Category

If you are creating a new collapsed category, provide a name for that category here.  In the displayed example, the new category will be called “OTHER”.


Choose an Action

If you want to collapse the selected rows/columns together into a single category, choose “Create New Collapsed Category.”   To convert the select rows/columns to missing data, choose “Convert to Missing Data (Drop).”


OK Button

Once you click on the OK button, your table will appear with the desired changes.


Cancel Button

Click on the Cancel button to return to your table without making any changes.


Column Variable Categories

The categories of the column variable will appear here.  In the displayed example, the column variable is IDEOLOGY, which has three categories—Liberal, Moderate, and Conserv.


Row Variable Categories

The categories of the row variable will appear here.  In the displayed example, the row variable is TV PREZ, which now has three categories—Much +, Some, and Not Much.


Missing Data

This row/column shows the number of missing cases at each level of the variable.


Dependent Variable

The dependent variable will appear along the vertical (y) axis.  ALCOHOL is the dependent variable in the displayed example.


Independent Variable

The independent variable will appear along the horizontal (x) axis.  MARRIAGE is the independent variable in the displayed example.


Scatterplot

The scatterplot will appear here.  For each case, a dot is placed at the intersection of its values on the independent and dependent variables.


Dependent Variable

If the values of a variable are assumed to have been partially affected, or caused, by the values of another variable, then that variable is called a dependent variable.  For example, if we assume that educational attainment has an effect on an individual’s income, then income would be the dependent variable.


Independent Variable

If the values of a variable are assumed to affect, or cause, the values of another variable, that variable is called the independent variable.  For example, if we assume that educational attainment affects an individual’s income, then educational attainment would be the independent variable.


X-Axis

In scatterplots, the x-axis is the horizontal axis and usually represents the independent variable.


Y-Axis

In scatterplots, the y-axis is the vertical axis and usually represents the dependent variable.


Regression Line

The regression equation describes the line (or plane) that best predicts the values of the dependent variable from the values of the independent variable.


Residual

The residual is the difference between the observed value of a variable and the value predicted using least squares regression with one or more independent variables.


Outlier

The value of a correlation coefficient may be strongly affected by the presence of a deviant case, or outlier.  In the Scatterplot task, an outlier is defined as the case that has the greatest effect on the correlation coefficient; removal of the outlier would change the correlation coefficient by the greatest amount.


Regression Equation

The regression equation will appear below your scatterplot.  The regression equation describes the line (or plane) that best predicts the values of the dependent variable from the values of the independent variable.  The regression equation is also displayed as a line in your scatterplot.


Scatterplot

The scatterplot will appear here.  For each case, a dot is placed at the intersection of its values on the independent and dependent variables.  The regression line will appear as a green line.


Scatterplot

The scatterplot will appear here.  For each case, a dot is placed at the intersection of its values on the independent and dependent variables.  The regression line will appear as a green line.  Purple lines will show the residual for each case, i.e. the distance between each case and the regression line.


Case Names

A list of the cases in your data file will appear here.  To find a case, click on its name.  A check mark will appear next to the selected case name.

In the displayed example, the user has selected “NEW HAMPSHIRE.”


OK Button

Click on the OK Button to return to your scatterplot with the selected case highlighted.


Cancel Button

Click on the Cancel Button to return to your scatterplot without highlighting a case.


Name of the Selected Case

The name of the selected case will appear here.  In the displayed example, the user has selected “NEW HAMPSHIRE.”


Value on the Independent Variable

The value of the selected case on the independent variable (x) will appear here.  In the displayed example, NEW HAMPSHIRE has a value of 10.2 on the independent variable.


Value on the Dependent Variable

The value of the selected case on the dependent variable (y) will appear here.  In the displayed example, NEW HAMPSHIRE has a value of 52.0 on the dependent variable.


New r Value if Removed

The value of the correlation coefficient (r) if the selected case were removed will be displayed here, along with its p-value.  In the displayed example, the correlation between ALCOHOL and MARRIAGE would change from .560 to .611 if NEW HAMPSHIRE were removed.


Selected Case

A red box will be drawn around the selected case.


Name of the Selected Outlier

The name of the outlier will appear here.  In the displayed example, the most deviant case is NEVADA.


Value on the Independent Variable

The value of the outlier on the independent variable (x) will appear here.  In the displayed example, NEVADA has a value of 106.3 on the independent variable.


Value on the Dependent Variable

The value of the outlier on the dependent variable (y) will appear here.  In the displayed example, NEVADA has a value of 60.69 on the dependent variable.


New r Value if Removed

The value of the correlation coefficient (r) if the outlier were removed will be displayed here, along with its p-value.  In the displayed example, the correlation between ALCOHOL and MARRIAGE would no longer be significant if NEVADA were removed.


Listwise Deletion

In listwise deletion of missing data, a case containing missing data will be omitted from all calculations.


Pairwise Deletion

In pairwise deletion, a case with missing data is omitted only from the calculations directly involving the variable(s) with missing data; the case is included in calculations in which these variables are not directly involved.


Cronbach's Alpha

Cronbach’s Alpha is a measure of the internal consistency of items, or reliability.  Frequently, you can create a better measure of a concept by combining several variables.  When you do this, you want to be sure that the items do, in fact, fit together.  Alpha can range from zero (no internal consistency) to unity (perfect internal consistency).


Test of Significance

Statistical significance refers to the probability that a given value of a statistic could have been observed in the sample, if there was no relationship in the population from which the sample was drawn.  Or, more simply, it is the likelihood that the results could have occurred by chance.  Typically, scientists require that results are significant at the .05 level; however, some use the more stringent criterion of .01.  A single asterisk will follow a statistic which is significant at the .05 level (*).  A double asterisk will follow a statistic which is significant at the .01 level (**).


Missing Data Deletion Options

Click here to switch between pairwise and listwise deletion of missing data.


Significance Test Options

Click here to switch between one-tailed and two-tailed tests of significance for the correlation coefficient.


Pairwise of Listwise Deletion

This area will indicate whether the correlation matrix uses pairwise or listwise deletion.


Type of Significance Test

This area will indicate whether the correlation matrix is using one-tailed or two-tailed tests of significance.


Significance Levels

As this note indicates, coefficients significant at the .05 level will be marked with one asterisk (*) and coefficients significant at the .01 level will be marked with two asterisks (**).


Variable Names

Variable names will appear here.  To find the correlation between two variables, find the intersection of a row variable and a column variable.


Correlation Coefficients

The correlation coefficients will appear here.  Correlation coefficients significant at the .05 level will be marked with one asterisk (*) and correlation coefficients significant at the .01 level will be marked with two asterisks (**).  The number of valid cases for each coefficient will appear below it in parentheses.


Correlation Coefficients

The correlation coefficients will appear here.  Correlation coefficients significant at the .05 level will be marked with one asterisk (*) and correlation coefficients significant at the .01 level will be marked with two asterisks (**).


Cronbach's Alpha

Cronbach’s Alpha is a measure of the internal consistency of items, or reliability.  Frequently, you can create a better measure of a concept by combining several variables.  When you do this, you want to be sure that the items do, in fact, fit together.  Alpha can range from zero (no internal consistency) to unity (perfect internal consistency).  Cronbach’s Alpha will only be calculated when listwise deletion is used.


Multiple R-Squared

The value of multiple R-squared indicates the proportion of variation in the dependent variable explained by the set of independent variables.


Independent Variables

The independent variables will appear here.


Dependent Variable

The dependent variable will appear here.


Standardized Beta

The beta coefficient is the standardized regression coefficient.  It tells us how many standard deviations of change we should observe in the dependent variable for each standard deviation of change in the independent variable, provided all other independent variables remained unchanged.


Unstandarized Beta

The unstandardized beta expresses the net effect of each independent variable after the effects of all other independent variables have been removed.  For example, an unstandardized beta of 117.98 indicates that for each one-unit change in the independent variable we would predict 117.98 units of change in the dependent variable (assuming all other independent variables remain unchanged).  Unstandardized betas are expressed in terms of the original units of measurement in the raw data.  Therefore, unstandardized betas should not be directly compared to determine which has the greatest effect on the dependent variable.


Mean Square

The mean square is a sum of squares divided by the appropriate degrees of freedom.  The F-ratio is the ratio of two mean squares.  These are used in analysis of variance.


F Ratio

 The ratio of two mean squares is called the F ratio and is used for testing statistical significance.


Regression Sum of Squares

The regression sum of squares is the variation in the dependent variable which can be attributed to the linear effect of the independent variable(s).


Residual Sum of Squares

The residual sum of squares is the amount of variation which remains in the dependent variable after the linear effect of the independent variable(s) has been removed.


Residuals

The difference between the observed value of a variable and the value predicted using least squares regression with one or more independent variables.


Regression Graph

Click here to view a graphic showing the standardized beta coefficients, the bivariate correlation coefficients, and the multiple R-squared.


ANOVA Statistics

Click here to see the standardized and unstandardized regression coefficients, the standard errors of the coefficients, and their statistical significance.  The ANOVA screen also partitions the sum of squares into regression sum of squares and residual sum of squares.


Correlation Matrix

Click here to see the correlation matrix for your variables.


Means

Click here to see the mean, standard deviation and number of cases for each of your variables.


Dummy Variable

A dummy variable is a variable with values of 0 and 1.  Dummy variables are typically used to introduce nominal variables into regression and correlation analyses.


Y-Intercept

The Y-Intercept is the place where the least squares regression line cross the Y-axis.


Total Sum of Squares

The total sum of squares is the variation of the dependent variable.


t-statistic

The t-statistic is used for testing the significance of a regression coefficient.  It is equivalent to dividing the unstandardized beta by its standard error.


Standard Error

The standard error of each unstandardized coefficient will appear here.


Source of Analysis of Variance Statistics

The source of each line of ANOVA statistics will appear here—regression, residual or total.


Cronbach's Alpha

Cronbach’s Alpha is a measure of the internal consistency of items, or reliability.  Frequently, you can create a better measure of a concept by combining several variables.  When you do this, you want to be sure that the items do, in fact, fit together.  Alpha can range from zero (no internal consistency) to unity (perfect internal consistency).  Cronbach’s Alpha will only be calculated if all correlations are positive.


Test of Significance

The correlation matrix will use a  one-tailed test to determine the significance of each coefficient.


Variable Names

Variable names will appear here.


Box-and-Whisker Diagram

A box-and-whisker diagram is shown in the Analysis of Variance and t-test tasks.  Each case is represented by a dot placed at the intersection of its values on the two variables.  For each level of the independent variable, a small horizontal line is drawn representing the mean of the dependent variable for that level, and a box is drawn which goes from one standard deviation below the mean to one standard deviation above the mean.  Lines connect the means of the groups.


Between Variation

In the Analysis of Variance task, the between sum of squares represents the amount of variation in the dependent variable which can be attributed to differences across levels of the independent variable, i.e., the amount of variation “caused” by the independent variable.


Within Variation

In the Analysis of Variance tasks, the within sum of squares represents the amount of variation in the dependent variable which cannot be attributed to differences across levels of the independent variable, i.e., the amount of variation “left over” after the effect of the independent variable has been removed.


ANOVA/t-test Graph

Click here to see a box-and-whisker diagram.


ANOVA Statistics

The ANOVA screen partitions the total sum of squares into that created by variation around the mean within each group (i.e., within) and that created by variation of the group around the overall mean (i.e. between).


Dependent Variable

The dependent variable will appear here.  In the displayed example, the dependent variable is LK CLINTON—how much the respondent likes Bill Clinton.


Independent Variable

The independent variable will appear here.  In the displayed example, the independent variable is SEX, with two categories—Male and Female.


Overall Mean

 The overall mean for the dependent variable will appear here.  In the displayed example the mean of LK CLINTON, for all respondents, was 5.765.


Eta Squared

Eta squared is a measure of association for use with ratio dependent variables and categorical independent variables.


Test of Nonlinearity

A test of nonlinearity is provided with the ANOVA statistics.  If the relationship between the two variables were linear, then the line shown in the box-and-whisker diagram would connect means across groups in a straight line; the statistical results would be the same as those generated by linear regression.  However, if this line is not straight, then we can test for a significant non-linear component in the relationship by comparing Eta squared with the R-squared; an F test is used to test for statistical significance.


Source of Analysis of Variance Statistics

The source of each line of ANOVA statistics will appear here—between, within, and total.


Statistical Significance of Differences in Means

The means display will tell you whether the differences in means across the categories of the independent variable are statistically significant.  In the displayed example, there are significant differences in the mean of LK CLINTON across categories of SEX.


Independent Variable

The name of the independent variable will appear here.


Variable Names

The variable names will appear here.  In the displayed example, the historical trends graph is showing two variables--% URBAN and % NO HS.  The color of each variable name is the color of its line on the graph.


Historical Trends Graph

The graph will appear here. The x-axis will be the range of years of available data for the selected variables.  In other words, if the selected variables have data available from 1950 to 2000, the x-axis will range from 1950 to 2000.  The y-axis will range from the lowest value on the displayed variables to the highest value on the displayed variables.  For each variable, a dot will be placed at each year for which data is available at its value on the y-axis.  A colored line will then connect the dots, providing a visual display of change in the variable over time.


Years

The x-axis will be the range of years of available data for the selected variables.  In other words, if the selected variables have data available from 1950 to 2000, the x-axis will range from 1950 to 2000.


Historical Events

A list of historical events, such a presidential elections, world wars, inventions, etc., will appear below your historical trends graph.  The included events may change from file to file.  When you click on an event, a red line will appear on your trends graph, allowing you to examine how that event may have influenced your variables.

In the displayed example, the user has selected the 1944 Presidential election between Roosevelt and Dewey.  Note that a red line appears on the trends graph at the year 1944.


Historical Event Line

When you click on a historical event from the list below the trends graph, a red line will appear on the graph at the year the event took place.   In the displayed example, the user has selected the 1944 Presidential election between Roosevelt and Dewey.  Therefore, a red line appears on the trends graph at 1944.


Scroll bar

Click on the scroll bar to scroll through the list of historical events.


Date Variable

A date variable is a variable for which each value is a date.  For example, each value of a date variable might be a year, such as “1901” or “1980.”  A date variable is required for examining historical trends.


Integer Data

A variable with integer data is composed of whole numbers.  In other words, cases have integer values such as 1, 2, etc.  A variable with decimal data has values such as 1.45, 5.67, etc.


Decimal Data

A variable with decimal data has values which include decimals, such as 1.45, 5.67, etc.  A variable with integer data has values which are whole numbers, such as 1, 2, 3, etc.


Row Variable

The name of the row variable will appear here.


Column Variable

The name of the column variable will appear here.


Overall Mean

The overall mean for the dependent variable will appear here.  In the displayed example the mean of LK CLINTON, for all respondents, was 59.343.


File & Data Menu

To access File and Data tasks in Student MicroCase, choose the File & Data Task Menu and then select the task of interest.

The following file and data management tasks are available:

  Opening files

  Creating new files

  Viewing file settings

  Defining and editing variables

  Collapsing variables

  Entering data

  Recoding variables

  Listing data

  Viewing a codebook

  Saving a File


Collapsing Variables, Step 1

At times you may wish to combine categories of an existing variable to create a new variable.  For example, if you had a variable which recorded the number of days per week the respondent watches the network news on television, you could collapse the variable into a smaller number of categories.  The resulting variable might have three categories—0 days,  1-6 days, and every day.

MicroCase provides a simple procedure for collapsing variables.  Once you have selected a variable to collapse, MicroCase will show a bar graph.  You can then create categories for your new variable and simply click on bars of the source variable to add them to that category.

The first step in collapsing a variable is choosing the variable you wish to collapse.  Choose the Collapse task from the File & Data menu.  A box will then appear in which you can select the variable to collapse.  Click on the screen shot below for more information.  For example, click on the Search button to see what it does.

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  Click here for step 2


Collapsing Variables, Step 2

Once you have selected a variable to collapse, a screen will appear  which allows you to assign categories of that variable to categories of a new variable.

The top of the screen will show a bar graph of the original variable.  To assign categories to a new variable, choose a new category and then click on the bars you wish to assign to it.  When you click on a new category, you can type a new name for that category.

When you have finished assigning categories to your new variable, click on the Finish button on the left hand side of your screen to continue to step 3.

Click on the screen shot below for more information.  For example, click on the area titled "Distribution of New Variable" to learn more about it.

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  Click here for step 3


Collapsing Variables, Step 3

The final step in collapsing a variable is to provide a name and description for your new variable and to verify that you have collapsed it as desired.

Provide a variable name and edit the variable description and category labels as desired.  Click on the OK button to create your new collapsed variable.  Click on the Cancel button to close this box without creating a new variable.

Click on the screen shot below for more information.  For example, click on the Recode Information box to see a description of its contents.

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Recode Information

Information about the collapse, including the categories of the original variable included in each category of the new variable, will be presented here.


Variable Range

MicroCase will define the range of your new variable based on the categories you defined.  The minimum and maximum values will be displayed here.


OK Button

Click on this button to create your new collapsed variable.


Cancel Button

Click on the Cancel button to close this box without creating a new variable.


Variable Description

MicroCase will provide a default variable description for you.  Edit the variable description as necessary in this box.


Category Labels

The category labels of your new variable will appear here.  You can edit the labels as necessary.  Next to each category will be the number of cases which have been assigned to it.


Source Variable Bars

A bar graph of the variable to be collapsed will appear here.  Click on bars to assign them to categories of your new variable.


Bar Information

As you move mouse pointers over the bar graph, information about each bar, including its value, frequency, percentage and category label, will appear here.


New Categories

To assign categories of the source variable to a category of your new variable, click on a category here.  Once you have clicked on a new category, clicking on the bar graph will assign categories of the source variable to it.  You may also provide a label for a new category once you have clicked on it.


New Category Colors

Each new category has an associated color.  When you click on the distribution of the source variable, the bars will change to the color of the selected new category.


Distribution of New Variable

As you assign categories of the source variable to categories of your new variable, the distribution of the new variable will appear here.


Collapsed Into

When you click on a category of the new variable, the categories which have been collapsed into it will appear here.  In the displayed example, the user has selected new category 9.  No categories have been collapsed into it.


Missing Data Information

This area will show both the number of missing cases the original variable has and the number of cases which are still unassigned to the new variable.  Any cases which are left unassigned will be converted to missing data in the new variable.


Collapsing Integer Variables

TO DO: Enter topic text here!


Collapsing Decimal Variables

TO DO: Enter topic text here!


Listing Data

Use the List Data task if you want to see the value of a variable by case.  In other words, use the List Data task if you want to see what value a particular case or cases has on a variable.   To list data, choose the List Data task from the File & Data menu.

A box will then appear in which you can indicate whether or not you wish to use "Question Display."  If you choose to enable question display, the variable description and category labels, if applicable,  will be displayed above your data list.  When you click on a cell in your data list, the correct category label, if applicable,  will be highlighted.

Click on the OK button to confirm your choice and list your data. Data will be presented in a spreadsheet format, with variables as columns and cases as rows.

Click on the screen shot below for more information about listing data.  For example, click on the Cancel button to see what it does.

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Enable Question Display

If you choose to enable question display, the variable description and category labels, if applicable,  will be displayed above your data list.  When you click on a cell in your data list, the correct category label, if applicable,  will be highlighted.


OK Button

Click on the OK button to list data with the options you selected.


Cancel Button

Click on the Cancel button to close this box without listing data.


Defining & Editing Variables

To add a new variable to your data file, choose the Define & Edit Variables task from the File & Data Task Menu.  The variable definition screen will then appear.

	On the left hand-side of the screen will be a box showing the current variable number and buttons which allow you to insert, and delete variables.   By default, MicroCase assumes that you want to add a new variable to the end of your file.  Thus, the variable number shown will be one higher than the number of variables currently in your file—i.e. if your file has 6 variables, the program assumes you wish to add variable 7. To edit an existing variable, click on the arrows beneath the variable number to find the desired variable.  To delete an existing variable, click on the arrows beneath the variable number to find the variable you wish to delete and then click on the Delete button.   If you want to add a new variable to somewhere in the middle of your file, click on the arrows beneath the variable number to scroll to the correct variable number and then click on the “Insert” button.  MicroCase will then insert a new variable before the variable number you selected.  In other words, if you scroll to variable number 6 and then click on “Insert,” your new variable will be number 6 and all subsequent variables will increase by one number.

Click on the screen shot above to learn more about the variable selection box.  For example, click on the “Delete” button to see what it does.

  Click here to learn about adding a name, description and category labels


Deleting Variables

To delete a variable, use the Define & Edit Variables task.  Once the variable definition screen has appeared, use the arrows to scroll to the variable number you want to delete, and then click on the Delete button.


Variable Number

This box will show the current variable number.  In the displayed example, the user is defining/editing variable number 2.


Variable Selection Arrows

Click on these arrows to scroll up or down through the variables in your data file.


Insert Button

Click on the Insert Button to insert a new variable into your file before the selected variable.  In the displayed example, clicking on the Insert Button would insert a new variable at number 2 and increase all subsequent variables by one number.  In Student MicroCase only a limited number of new variables can be defined..


Delete  Button

Click on the Delete Button to delete the selected variable.  In the displayed example, clicking on the Delete Button would delete variable number 2.

In Student MicroCase, only a limited number of new variables may be defined.  After you have defined these variables, you must first delete an existing variable before you can add a new one.


Adding a variable name, description, and category labels

For each variable you create, you need to provide a variable name.  The variable name must be 10 or fewer characters in length; it may not start with a number and it may not contain a quotation mark (“).  Special characters ($, #, %, etc.), numbers, spaces, periods, and upper- and lower-case letters can be used in the variable name.

Variable descriptions are optional.  In the full retail version of MicroCase, variable descriptions are limited to 2,000 characters or less.  In student versions of MicroCase, variable descriptions are limited to 255 characters or less.  There are no limitations on the kinds of characters which can be used in the description.

Use the Minimum and Maximum boxes to indicate the range of your variable, if necessary.  If your variable will contain decimal data, use the box titled "Decimal Digits" to indicate how many digits will appear after the decimal—i.e. if your data is of the format "1.32," then you have two decimal digits.

If your minimum and maximum values are integers (i.e. no decimals) and you have 10 or fewer categories, you have the option of entering category labels.  Once you have a provided a minimum and maximum value, a series of boxes will appear in which you can enter your category labels.  For example, if you want to create a new variable with three categories--Clinton, Bush, and Perot—provide a minimum value of 1 and a maximum value of 3.  Three boxes will then appear, to the right of the minimum and maximum boxes, in which you can enter those category labels.

Once you are done defining or editing your variable, click on the Continue Button to save it.  You will then move to the next variable in your data set, or the program will provide you with a blank variable if you are at the end of your file.  You can click on the Reset Button at any time to undo any changes you have made.  Click on the Menu Button at any time to return to the Task Selection Menu .

Click on the screen shot below for more information about defining variables.  For example, click on the Reset Button to see what it does.

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Variable Name

Enter or edit the variable name in this box.  The variable name must be 10 or fewer characters in length; it may not start with a number and it may not contain a quotation mark (“).  Special characters ($, #, %, etc.), numbers, spaces, periods, and upper- and lower-case letters can be used in the variable name.


Variable Description

Enter or edit the variable description in this box.  Variable descriptions are optional.  In the full version of MicroCase, variable descriptions are limited to 2,000 characters or less.  In student versions of MicroCase, variable descriptions are limited to 255 characters or less.  There are no limitations on the kinds of characters which can be used in the description.


Continue Button

Once you are done defining or editing  your variable, click on the Continue Button to save it.  You will then move to the next variable in your data set, or the program will provide you with a blank variable if you are at the end of your file.


Reset Button

Click on the Reset Button to undo any changes you have made to the current variable.


Spell Checking

This option is not available in student versions of MicroCase.


Edit Recode

This option is not available in student versions of MicroCase.


Range Checking

If you want MicroCase to check that entered data falls within the minimum and maximum values you have provided, check this box.  Any values which do not fall within the minimum and maximum will be converted to missing data.


Category Labels

Enter category labels (optional) in the boxes which appear here.  Once you have provided a minimum and maximum value, the correct number of boxes will appear.  You cannot enter category labels for decimal data.  In the displayed example, the user has entered three category labels—1= Clinton, 2 = Bush, and  3=Perot.


Minimum Value

Enter the minimum value of your variable in this box.  For example, if your variable will range from 1 to 3, enter a "1" in this box.


Maximum Value

Enter the maximum value of your variable in this box.  For example, if your variable will range from 1 to 3, enter a "3" in this box.


Decimal Digits

Enter the number of decimal digits (if any) you want your variable to have in this box.  For example, if you want this variable to have two decimal places, i.e. "10.35," enter a "2" in this box.


Entering Data

To enter new data, or verify data using rekey verification, choose the Enter Data task from the File & Data menu.  A box will then appear in which you can set data entry options.

You can enter data in one of two ways, question entry or grid entry.  If you choose grid entry, you will enter data in a grid or spreadsheet format, in which cases are rows and variables are columns.  To enter data for a particular case or variable, simply type into the proper cell.  Hit the Enter or Tab key to move from cell to cell, or click on any cell with the mouse to move to it.

If you choose to enter data using question entry (with grid), a box will appear above the grid which shows the variable name, description and category labels.  Simply click on a category label and MicroCase will insert the correct number for you and move to the next cell.

Question entry (by case) also allows you to enter data by clicking on category labels.  In question entry (by case), however, the data grid is hidden from view and the variable description is provided in a larger font.  Entering data using question entry (by case) is quite similar to completing a questionnaire.

If you have already entered data and want to verify it using rekey verification, click on the "Enable Rekey Verification" box.  If the data you enter does not match the existing data, a box will appear which asks you which value is correct.

Once you have selected your data entry options, click on the OK button to begin data entry.

Click on the screen shot below for more information.  For example, click on the Cancel button to see what it does.

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Click on a button below to learn more about specific data entry options:

  Grid entry

  Question entry (by case)

  Question entry (with grid)

  Rekey verification


Grid Entry

Click here to use the grid entry option while entering data.  If you choose grid entry, you will enter data in a grid or spreadsheet format, in which cases are rows and variables are columns.  To enter data for a particular case or variable, simply enter data into the proper cell.  Hit the Enter or Tab key to move from cell to cell, or click on any cell with the mouse to move to it.


Save Data

Once you click on the Menu button, MicroCase will ask you if you want to save the data you have entered.  Click on "Yes" to save your entered data.  Click on "No" to return to the main menu without saving the data you have entered.

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Rekey Verification

If you have already entered data and want to verify it using rekey verification, click on the "Enable Rekey Verification" box to check it. If the data you enter does not match the existing data, a box will appear which asks you which value is correct.


OK Button

Click on the OK button to begin data entry using the selected options.


Cancel Button

Click on the Cancel button to close this box without entering data.


Entering Data Using Grid Entry

If you choose to the Grid Entry option when initiating the Enter Data task, you will enter data by typing values into a grid in which rows are cases and variables are columns.

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To enter data for a particular case or variable, simply type into the proper cell.  Hit the Enter or Tab key to move from cell to cell, or click on any cell with the mouse.

To cut, copy and paste values, right-click on a row, column, or cell with the mouse.  A menu will then appear in which you can choose the desired function.

When you have finished entering data, click on the Menu button.  MicroCase will then ask if you want to save your data.  Click "Yes" to save the data you have entered and return to the File & Data menu.  Click on "No" if you do not want to save the data you entered.

  See also


Entering Data Using Question Entry (with Grid)

If you choose to the Question Entry option when initiating the Enter Data task, you will enter data as if filling out a questionnaire.  Your data will appear in a grid with cases as rows and variables as columns.  The variable name, description and category labels for the current variable will appear above this grid.

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To enter data, simply double-click on the proper category (if the variable is categorical) or enter data into the box which appears (if the variable is alphanumeric or decimal).  To enter missing data, choose "[blank]" for categorical variables or just hit the Enter key when entering alphanumeric or decimal data.

Once you have provided an answer, MicroCase will enter data into the proper cell for you and move to the next variable.  Once you have entered data for all variables for a particular case, MicroCase will move to the next case.

To quickly jump to a particular case or variable, click on a cell with the mouse, or move from cell to cell by hitting the Enter or Tab key.

To cut, copy and paste values, right-click on a row, column, or cell with the mouse.  A menu will then appear in which you can choose the desired function.

When you have finished entering data, click on the Menu button.  MicroCase will then ask if you want to save your data.  Click "Yes" to save the data you have entered and return to the File & Data menu.  Click on "No" if you do not want to save the data you entered.

  See also


Entering Data using Question Entry (by Case)

If you choose to the Question Entry (by case) option when initiating the Enter Data task, you will enter data as if filling out a questionnaire.  The variable description will appear at the top of your screen in a large, easy-to-read font.  The category labels for the current variable will appear in the center of your screen.

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To enter data, simply double-click on the proper category (if the variable is categorical) or enter data into the box which appears (if the variable is alphanumeric or decimal).  To enter missing data, choose "[blank]" for categorical variables or just hit the Enter key when entering alphanumeric or decimal data.

Once you have provided an answer, MicroCase will move to the next variable.  Once you have entered data for all variables for a particular case, MicroCase will automatically move to the next case.

When you have finished entering data, click on the Menu button.  MicroCase will then ask if you want to save your data.  Click "Yes" to save the data you have entered.  Click on "No" if you do not want to save the data you entered.

  See also


Using Rekey Verification

If you enable rekey verification when initiating the Enter Data task, MicroCase will inform you whenever the data you enter does not match existing data.  For example, if you want to verify the consistency of entered data, you could have the same data entered twice by two different data entry clerks.  When rekeyed data does not match the data previously entered, a box will appear informing you of the mismatch.

The box that appears will show both the existing value of the case and the new value you have entered.   You can then choose which value to use and click on the OK button.  MicroCase will insert the chosen value into the data grid for you.

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  See also


Viewing a Codebook

To view a codebook for your data file, choose the Codebook task from the File & Data menu.  A box will then appear in which you can set several options.

First, you can either view a codebook for all of the variables in your data file, or for selected variables.  If you choose the selected variables option, a box will appear in which you can select the variables to include in the codebook.  Click here for help with selecting variables.

Second, you can choose a stratification variable, if you wish.  If you choose a stratification variable, the univariate distribution for each variable will be shown separately for cases which fall in each level of the stratification variable.  For example, if you stratify by sex, variable distributions will be shown separately for males and females.  To stratify your codebook, click on the "Stratify" box to check it.  You will then be asked to select the variable you want to use to stratify the codebook.  Click here for help with selecting a variable.

The subset option is not available in student versions of MicroCase.

Once you have chosen variables and selected a stratification variable if necessary, click on the OK button to view your codebook.

Click on the screen shot below for more information.  For example, click on the Settings button to see what it does.

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  Click here to learn about changing codebook settings

  Click here to see sample codebook output


View All Variables

Choose this option to view a codebook for all of the variables in your data file.


View Selected Variables

Choose this option if you want to view a codebook for selected variables from your data file.  A box will then appear in which you can select the variables to include in the codebook.


Stratify Codebook

To stratify your codebook, click on the "Stratify" box to check it.  You will then be asked to select the variable you want to use to stratify the codebook.  If you choose a stratification variable, the univariate distribution for each variable will be shown separately for cases which fall in each level of the stratification variable.  For example, if you stratify by sex, distributions will be shown separately for males and females.


View Codebook for Subset of Cases

This option is not available in student versions of MicroCase.


OK Button

Once you have chosen variables and selected a stratification variable if necessary, click on the OK button to view your codebook.


Cancel Button

Click on the Cancel button to close this box without viewing a codebook.


Recoding Variables

Use the Recode Variables task if you want to create a new variable based on the values of other variables.  You can use recodes to create indexes, typologies, rates, and transformed variables, such as z-scores.

To create a variable with a recode, choose the Recode Variables task from the File & Data Task Menu.  A box will then appear which allows you to choose from eight different types of recodes.  Three of those recodes, Lag/Difference, Custom, and Recode Macro, are only available in the full version of MicroCase.

Once the Recode Task box has appeared, click on the button corresponding to the type of recode you wish to perform.  The program will then walk you through a series of steps for creating the chosen recode.

Click on the screen shot below to learn more about choosing a recode.  For example, click on the Variable List button to see what it does.

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Click on a button below to learn more about a particular recode:

  Sum recode

  Rate recode

  Typology recode

  Rank recode

  Transform Variables recode


Sum Recode, Step 1

Use the sum recode to create a new variable which assigns each case the average or sum of its values on other variables.  For example, if you have five items which ask respondents about their attitudes on abortion, you could add those responses together to create an abortion index.

The first step in creating a sum recode is to tell MicroCase how you wish variables to be combined and how you want missing data to be handled.  There are four different options available for combining variables—you can sum the values of the variables, compute the average value of a group of variables (the sum divided by the number of variables), count the number of variables with non-zero values, or compute the proportion of variables with non-zero values.

There are three different ways to handle missing data.  You can have MicroCase assign no value (i.e. missing data) to a case if it has missing data on any of the source variables, replace missing data with zero in all calculations, or ignore missing data completely.

Once you have made your selections, click on the Next button to move to step 2.

Click on the screen shot below for more information about step 1 of the sum recode.  For example, click on the Help button to see what it does.

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  Click here for step 2


Sum/Index Options

Choose from these four options the method by which you want to have your variables combined--you can sum the values of the variables, compute the average value of a group of variables (the sum divided by the number of variables), count the number of variables with non-zero values, or compute the proportion of variables with non-zero values.


Missing Data Options

Choose from these three options the method by which you want missing data to be handled.  You can have MicroCase assign no value (i.e. missing data) to a case if it has missing data on any of the source variables, replace missing data with zero in all calculations, or ignore missing data completely.


Back Button

You can click on the Back button to move back one step while creating a recode.  The Back button will not be available in the first step of your recode.


Next Button

Click on the Next button to move to the next step in your recode task.


Cancel Button

Click on the Cancel button if you decide you do not want to continue with a recode.


Help Button

Click on the Help Button to receive help for the current step of your recode task.


Sum Recode, Step 2

The second step in creating a sum/index recode is to choose the variables you wish to use in creating that sum or index.

From the list of variables in your data file, select the variables to be used in your recode.  A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on the selection arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter.  You can also select multiple variables at once by highlighting them and clicking on the selection arrow.  Once you have chosen variables, click on the Next button to move to step 3.

Click on the screen shot below to learn more about step 2.  For example, click on the Search button to see what it does.

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  Click here for step 3


List of Selected Variables

The list of variables you have selected will appear here.  In the displayed example, the user has selected six variables.  To remove a variable from your list of selected variables, click on it with the right mouse button and choose “Delete.”


List of Selected Variable Numbers

When you select a variable, its variable number will appear in this box.


Variable Selection Box

A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on the arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter.


Clear All Button

Click on the Clear All button to clear your list of selected variables.


Sum Recode, Step 3

The third step of the sum recode shows you a correlation matrix for your selected variables.

There are two functions you can perform during step 3—dropping variables and flipping/unflipping category values.  If, after viewing the correlation matrix, you want to drop a variable from the index, click on the variable name and then click on the button titled "Drop/add variable from list"

Often variables you wish to include in an index will have category levels which are in opposite directions.  For example, one variable might be coded so that a high value equals agree (1 = disagree, 2 = neither agree nor disagree, 3 = agree) and another so that a high value equals disagree (1 = agree, 2 = neither agree nor disagree, 3 = disagree).  MicroCase can automatically "flip" the categories of a variable for you so that they match the other variables in your sum/index.  To flip or unflip a variable's category values, click on a variable name and then click on the button titled "Flip/unflip category values."

Once you have viewed the correlation matrix and made and necessary corrections, click on the Next button to continue to step 4.

Click on the screen shot below for more information about step 3.  For example, click on the Back button to see what it does.

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  Click here for step 4


Variable List

A list of all the variables you selected will appear in this box.  If the box next to a variable name has a check mark, it will be included in the sum/index.  To remove a variable from the sum/index, click on its name and then click on the button titled "Drop/add variable from list."


Drop/Add Button

To drop a variable from your sum/index, click on its name and then click on the button titled "Drop/add variable from list."  When you drop a variable, the check next to its name will be removed.  If you want to return a variable the list, click on its name and click on the drop/add button again.


Flip/Unflip Category Values

Often variables you wish to include in an index will have category levels which are in opposite directions.  For example, one variable might be coded so that a high value equals agree (1 = disagree, 2 = neither agree nor disagree, 3 = agree) and another so that a high value equals disagree (1 = agree, 2 = neither agree nor disagree, 3 = disagree).  MicroCase can automatically "flip" the categories of a variable for you so that they match the other variables in your sum/index.  To flip or unflip a variable's category values, click on a variable name and then click on this button.


Correlation Matrix

The correlations between all of the included variables will be presented here.  If you have flipped category values of variables, the affected correlation coefficients will be color-coded.  If you drop a variable from the recode, it will be removed from the correlation matrix.


Variable Description

When you click on a variable name in the variable list, the variable description and category labels (if any) will appear in this box.


Cronbach's Alpha/Missing Data

The value of Cronbach's Alpha for your selected variables and the number of cases with missing data will be presented here.  Cronbach’s Alpha is a measure of the internal consistency of items, or reliability. Alpha can range from zero (no internal consistency) to unity (perfect internal consistency).


Sum Recode, Step 4

Step 4 of the sum/index recode asks you to provide a name and description for your new variable.  MicroCase will provide a default variable description which includes the names of all included variables, value of Cronbach's Alpha and number of cases with missing data.

Step 4 also shows you the results of your new recode case by case.  If, upon examining these results, you decide to change the recode, click on the Back button.

Once you have provided a variable name and have edited the variable description as necessary, click on the Next button to continue to step 5.

Click on the screen shot below for more information on step 4.  For example, click on the Back button to see what it does.

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  Click here for step 5


Variable Name

Enter a name for your new variable in this box.  The variable name must be 10 or fewer characters in length; it may not start with a number and it may not contain a quotation mark (“).  Special characters ($, #, %, etc.), numbers, spaces, periods, and upper- and lower-case letters can be used in the variable name.


Variable Description

By default, MicroCase will provide a description for your new variable which indicates the variables included in the recode and type of recode used.  You may edit/change this description as necessary.


Decimal Digits

Type the number of decimal digits you want your new variable to have into this box.


Case-by-Case Results

MicroCase will show you the results of your recode for each case so that you can ensure the recode was performed as desired.  Blank lines indicate that a case will have missing data on the new recode variable.  If, after viewing the case-by-case results, you decide to change the recode, click on the Back button.


Sum Recode, Step 5

Click on the Finish button to finalize the recode and create your new variable.  If you need to make changes to the recode, click on the Back button.

Click on the screen shot below for more information.  For example, click on the Finish button to see what it does.

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Finish Button

Click on the Finish button to create your new recode variable.


OK Button

Click here to close the Recode Task box.


Variable List Button

Click here to view a list of all the variables in your data file.


Variable Number

This box will show the variable number which will be assigned to your new recode.  Recodes will be added to the end of your data file.


Sum Recode Button

To create a new variable which assigns each case the average or sum of its values on other variables, click on the Sum/Index button.  For example, if you have five items which ask respondents about their attitudes on abortion, you could add those responses together to create an abortion index.


Rate Recode Button

If you want to use two variables  to create a rate, click on the Rate button.  For example, if you have a variable which provides the number of doctors per state and a variable which gives the population of each state, you could use the rate recode to create a new variable which is the number of doctors per 10,000 population.


Typology Button

The typology recode allows you to assign each case to a category of a new variable based on its values on other categorical variables.

Perhaps you have two variables which ask respondents whether they think women should work outside of the home when their children are newborns and whether women should work outside of the home when their children are in school.  One might consider someone who answers "no" to both questions to have a more conservative view of gender roles than someone who answers "yes" to both questions.  Someone who answers "yes" to one question and "no" to the other has a more moderate view of gender roles.

Using the typology recode, you could create this new "gender roles" variable by assigning categories of the new variable to different patterns of responses on the source variables.


Rank/Percentile Button

Use the rank/percentile recode to rank cases from low to high or from high to low based on their values on a variable.  For example, you could rank cases from low to high based on their values on an income variable.  The case with the lowest income would then receive a "1," the next lowest case would receive a "2," etc.  To perform a rank/percentile recode, click on this button.


Transform Variables Button

Click here to create a new variable that is a transformation of an existing variable.  You can use the transformation recode to create dummy variables, z-scores, squares, cubes, logs, square roots and reciprocals.


Lag/Difference Button

The lag/difference recode is used to create special variables for use in time series analysis.  This recode is not available in the student version of MicroCase.


Custom Recode Button

Use the custom recode function to create a new variable using standard equations, such as if/then statements and/or arithmetic operations. This recode is not available in the student version of MicroCase.


Recode Macro Button

If you plan to use the same equation to create a number of different variables, you can use the recode macro function to save those recode statements for later use. This recode is not available in the student version of MicroCase.


Rate Recode, Step 1

A rate is a proportion or ratio and is usually created by dividing one variable by another variable.  The purpose of rates is to create a common basis for comparing variable across aggregate units so as to control for differences in such factors as size.  For example, if you have a variable which provides the number of doctors per country and another variable which provides the population of each country, you can create a new variable which is the number of doctors per 10,000 population.

To create a rate recode, you need two variables--a variable to be used as the numerator and another to be used as the denominator.  The first step in creating the rate recode is to select a variable to be used as the numerator from a list of the variables in your data file.   A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on the selection arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter.

Population numbers are often adjusted by a factor of ten.  For example, instead of providing raw numbers, a population variable may give the population in 1,000s, 10,000s, etc.  If the variable you are using as the numerator is not in actual numbers (i.e. 1s), you need to tell MicroCase how to adjust that variable.  If necessary, choose a base for the numerator from the options provided.   Once you have chosen and adjusted the numerator variable as necessary, click on the Next button to move to step 2.

Click on the screen shot below for more information on step 1.  For example, click on the Next button to see what it does.

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  Click here for step 2


Adjust Numerator

Population numbers are often adjusted by a factor of ten.  For example, instead of providing raw numbers, a population variable may give the population in 1,000s, 10,000s, etc.  If the variable you are using as the numerator is not in actual numbers (i.e. 1s), you need to tell MicroCase how to adjust that variable.


Rate Recode, Step 2

To create a rate recode, you need two variables--a variable to be used as the numerator and another to be used as the denominator.  The second step in creating the rate recode is to select a variable to be used as the denominator from a list of the variables in your data file.   A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on the selection arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter.

Population numbers are often adjusted by a factor of ten.  For example, instead of providing raw numbers, a population variable may give the population in 1,000s, 10,000s, etc.  If the variable you are using as the denominator is not in actual numbers (i.e. 1s), you need to tell MicroCase how to adjust that variable.  If necessary, choose a base for the denominator from the options provided.   Once you have chosen and adjusted the denominator variable as necessary, click on the Next button to move to step 3.

Click on the screen shot below for more information on step 2.  For example, click on the Next button to see what it does.

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  Click here for step 3


Adjust Denominator

Population numbers are often adjusted by a factor of ten.  For example, instead of providing raw numbers, a population variable may give the population in 1,000s, 10,000s, etc.  If the variable you are using as the  denominator is not in actual numbers (i.e. 1s), you need to tell MicroCase how to adjust that variable.


Rate Recode, Step 3

The third step of the recode shows you the case by case results of your rate recode and allows you to adjust the multiplier as necessary.  For example if your rate were currently the number of doctors per 1,000 population, clicking on the right spinner arrow  would change it to the number of doctors per 10,000 population.

Once you have adjusted the recode as necessary, click on the Next button to continue to step 4.  Click on the Back button if you wish to change an earlier step of the recode.

Click on the screen shot below for more information on step 3.  For example, click on the spinner arrows to see what they do.

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  Click here for step 4


Spinner

Use these two arrows to adjust the multiplier of your rate by a factor of ten.  For example, if your rate were currently the number of doctors per 100 population, clicking on the right arrow would change it to the number of doctors per 1,000 population.


Rate Equation

This box will show the equation which will be used to create your rate.


Rate Interpretation

This box will provide the appropriate interpretation of the rate recode, based on the multiplier used and the base (i.e. 1s, 100s, 1,000s, etc.) of the numerator and denominator.


Rate Recode, Step 4

Step 4 of the rate recode asks you to provide a name and description for your new variable.  MicroCase will provide a default variable description which includes the names of all included variables, and the equation used to create the variable.

Once you have provided a variable name and have edited the variable description as necessary, click on the Next button to continue to step 5.

Click on the screen shot below for more information on step 4.  For example, click on the Back button to see what it does.

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  Click here for step 5


Rate Recode, Step 5

Click on the Finish button to finalize the recode and create your new variable.  If you need to make changes to the recode, click on the Back button.

Click on the screen shot below for more information.  For example, click on the Finish button to see what it does.

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Typology Recode, Step 1

The typology recode allows you to assign each case to a category of a new variable based on its values on other categorical variables.

Perhaps you have two variables which ask respondents whether they think women should work outside of the home when their children are below school age and whether women should work outside of the home when their children are in school.  One might consider someone who answers "no" to both questions to have a more traditional view of gender roles than someone who answers "yes" to both questions.  Someone who answers "yes" to one question and "no" to the other has a mixed view of gender roles.

Using the typology recode, you could create this new "sex roles" variable by assigning categories of the new variable to different patterns of responses on the source variables.

The first step in the typology recode is to define the new variable you wish to create by providing a name, description and category labels.  In the example below, the user is creating a new variable called "SEX ROLE," which will have three categories--TRADITION (traditional), MIXED, and MODERN.  Once you have provided a name, description and category labels, click on the Next button to continue to step 2.

Click on the screen shot below for more information on step 1.  For example, click on the Next button to see what it does.

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  Click here for step 2


Variable Description

Enter a variable description (optional) for your new typology variable in this box.


Category Labels

Type category labels for your new variable in these boxes.  For example, if your new variable will range from 1 to 3, type category labels in the boxes numbered 1 to 3.


Typology Recode, Step 2

The second step in creating a typology recode is to choose the variables you wish to use in creating the typology.

From the list of variables in your data file, select the variables to be used in your recode. You must select either two or three variables.   A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on a selection arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter.  Once you have chosen two or three variables, click on the Next button to move to step 3.

Click on the screen shot below to learn more about step 2.  For example, click on the Search button to see what it does.

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  Click here for step 3


Selection Arrow

Once you have clicked on a variable name in the variable list, click on this arrow to select it.


Typology Recode, Step 3

In step 3 of the typology recode you need to tell MicroCase which category of your new variable you want assigned to each combination of categories on the source variables.  If you leave a combination blank, it will be assigned missing data.

In the example below, cases with the value "YES" on the variable MA WORK<2 and YES on the variable MA WORK>5 will be assigned category 3 (MODERN) of the new "SEX ROLE "variable.  Cases with the value "NO" on both variables will be assigned category 1 (TRADITION) on the new variable.

Click on the screen shot below for more information on step 3.  For example, click on the Next button to see what it does.

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  Click here for step 4


Values on Source Variables

These boxes will show all of the combinations of categories on the source variables.  For each combination, enter the category number of the new variable you want assigned.

In the displayed example, cases with the value "YES" on the variable MA WORK<2 and YES on the variable MA WORK>5 will be assigned category 3 (MODERN) of the new "SEX ROLE "variable.  Cases with the value "NO" on both variables will be assigned category 1 (TRADITION) on the new variable.


# Column

In this column type the category number of the new variable you want assigned for each combination of categories of the source variables.  Leave a cell blank if you want missing data assigned to a particular combination of categories.


Assigned Category Label

Once you have typed a category number in the # column, the associated category label of the new variable will appear here.


Variable Name and Category Labels

The name of your new variable and its category labels will appear here.


Typology Recode, Step 4

Step 4 of the Typology recode shows you the results of your recode, case by case.  If, upon examining the results, you decide to change the recode, click on the Back button.  Click on the Next button to continue to step 5.

Click on the screen shot below for more information on step 4.  For example, click on the Next button to see what it does.

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  Click here for step 5


Typology Recode, Step 5

Click on the Finish button to finalize the recode and create your new variable.  If you need to make changes to the recode, click on the Back button.

Click on the screen shot below for more information.  For example, click on the Finish button to see what it does.

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Rank Recode, Step 1

Use the Rank recode to create a new variable in which the value of each case is its ranking, from low to high or high to low, on another variable.

The first step in creating a  rank recode is to choose the variable to be used in ranking cases and the manner in which cases should be ranked.

From the list of variables in your data file, select the variable to be ranked.  A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on a selection arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter.

From the list of ranking options, choose whether you want variables to be ranked or percentiled from high to low or low to high.  If you select ranking, you should also indicate how you want ties to be handled.  If two cases have the same value on the source variable, MicroCase can either assign each case the average of the tied ranks or assign both cases the lowest of the tied ranks.

Once you have chosen a variable and set your ranking options, click on the Next button to move to step 2.

Click on the screen shot below to learn more about step 1.  For example, click on the Search button to see what it does.

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  Click here for step 2


Ranking Options

Choose from these four options how you want cases to be ranked or percentiled.  If you choose to rank from high to low the case with the highest value will receive a 1.  If you choose to rank from low to high the case with the lowest value will receive a 1.


Treatment of Ties

Choose from these two options how you want ties to be handled.  If two cases have the same value on the source variable, MicroCase can either assign each case the average of the tied ranks or assign both cases the lowest of the tied ranks.  These options only apply to ranks, not percentiles.


Rank Recode, Step 2

Step 2 of the rank recode asks you to provide a name and description for your new variable.  MicroCase will provide a default variable description which includes the name of the source variable and type of recode used

Step 2 also shows you the results of your new recode case by case.  If, upon examining these results, you decide to change the recode, click on the Back button.

Once you have provided a variable name and have edited the variable description as necessary, click on the Next button to continue to step 3.

Click on the screen shot below for more information on step 2.  For example, click on the Back button to see what it does.

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  Click here for step 3


Rank Recode, Step 3

Click on the Finish button to finalize the recode and create your new variable.  If you need to make changes to the recode, click on the Back button.

Click on the screen shot below for more information.  For example, click on the Finish button to see what it does.

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Transform Variables Recode, Step 1

The transform variables recode is useful when you need to create a new variable that is a transformation of an existing variable.  For example, you might want to create a variable for which the value of each case is the square root of the source variable.  Using the transform variables recode you can generate dummy variables, z-scores, squares, cubes, logs, square roots and reciprocals.  Note: In the z-score recode, the standard deviation of the sample (not the estimated standard deviation of the population) is used in the z-score calculation.

The first step in creating a transformation is to select the source variable; i.e. the variable from which MicroCase will generate the transformed variable.

From the list of variables in your data file, select a variable.  A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on a selection arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter.

Once you have chosen a variable, choose the transformation you wish to create and then click on the Next button to continue to step 2.

Click on the screen shot below to learn more about step 1.  For example, click on the Search button to see what it does.

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  Click here for step 2


Transform Variables Recode, Step 2

Step 2 of the transform variables recode asks you to provide a name and description for your new variable.  MicroCase will provide a default variable description that includes the name and the type of transformation used.

If you are creating dummy variables a set of spinner arrows will appear.  Click on the arrows to scroll through your new dummy variables.

Step 2 also shows you the results of your new recode case by case.  If, upon examining these results, you decide to change the recode, click on the Back button.

Once you have provided a variable name and have edited the variable description as necessary, click on the Next button to continue to step 3.

Click on the screen shot below for more information on step 2.  For example, click on the Back button to see what it does.

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  Click here for step 3


Transform Variables Recode, Step 3

The final step in creating a recode is to tell MicroCase whether or not to save the recode information.  Click here to learn about the benefits of saving recode information.

Click on the Finish button to create your new transformed variable.  If you need to change the recode, click on the Back button.

Click on the screen shot below for more information.  For example, click on the Finish button to see what it does.

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Changing Codebook Settings

You can change codebook settings both while viewing a codebook and when you first choose the Codebook task from the File & Data menu.  Using the Codebook Settings box you can change how codebook information will be displayed.  For example, you can turn on or off the display of variable descriptions, set the number of decimal digits used for summary statistics, etc.

To change codebook settings, click on the Settings button.  The Codebook Settings box will then appear.  If an item is "checked" it will appear in your codebook display.  Once you have changed the settings as desired, click on the OK button to view the codebook.

Click on the screen shot below for more information.  For example, click on the Show Table check box for a description.

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Display Variable Number

If this box has a checkmark, variable numbers will be displayed in your codebook.  Click on this box to add or remove the checkmark.


Display Variable Name

If this box has a checkmark, variable names will be displayed in your codebook.  Click on this box to add or remove the checkmark.


Display Variable Description

If this box has a checkmark, variable descriptions will be displayed in your codebook.  Click on this box to add or remove the checkmark.


Display Variable Range

If this box has a checkmark, variable ranges will be displayed in your codebook.  Click on this box to add or remove the checkmark.


Display Distribution Table

If this box has a checkmark, MicroCase will display a univariate distribution table for each integer variable in your codebook.  Click on this box to add or remove the checkmark.


Maximum Number of Rows

Choose from these three options the maximum number of rows you want MicroCase to display for integer variables included in your codebook.  If a variable exceeds the maximum number of rows you set, only summary statistics (the mean, standard deviation and number of cases) will be displayed for that variable.


Category Numbers

Click on this box to choose the type of category numbers you want to use--values (i.e. 1, 2, 3), letters (i.e. a, b, c) or no category numbers.


Display Category Labels

If this box has a checkmark, short category labels will be displayed in your codebook.  Click on this box to add or remove the checkmark.


Display Frequencies

If this box has a checkmark, MicroCase will display frequencies in the distribution table.  Click on this box to add or remove the checkmark.


Display Percentages

If this box has a checkmark, MicroCase will display percentages in the distribution table.  Click on this box to add or remove the checkmark.


Percentage Decimal Digits

Enter into this box the number of decimal digits you want MicroCase to use for percentages in the distribution table.


Show Summary Statistics

If this box has a checkmark, MicroCase will display summary statistics (mean, standard deviation and number of cases) for all numeric variables that have too many categories to be displayed in a frequency table.


Summary Statistics Decimal Digits

Enter into this box the number of decimal digits you want MicroCase to use for the mean and standard deviation.


OK Button

Click on the OK button to close the Codebook Settings box and return to your codebook.  MicroCase will then display codebook items using the settings your provided.


Cancel Button

Click on the Cancel Button to close this box without making any changes to the codebook settings.


Sample Codebook Output

The following screen shot shows sample codebook output for a variable named LIKE CONG?  In this example, the user has stratified the codebook by SEX, therefore the distribution table shows the distribution of LIKE CONG? for males and females separately.

Click on the arrows under the variable number to cycle through your variables.  Click on the Settings button to change codebook settings .

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  Click here to learn about changing codebook settings


Variable Number

This box will show the number of the variable you are currently viewing.


Variable Selection Arrows

Click on these arrows to view the summary information for the next or previous variable number.


Settings Button

Click on this button to change the codebook settings. Using the Codebook Settings box you can change how codebook information will be displayed.  For example, you can turn on or off the display of variable descriptions, set the number of decimal digits used for summary statistics, etc.


Variable Name and Description

The variable name and description will appear here.  The display of this information will depend upon the codebook settings.  By default, MicroCase will display the variable number, name, and description (if any).  Click on the Settings buttons to change these settings.


Stratification Variable Information

If you have stratified your codebook, the name, number, and description of the stratification variable will appear here.


Variable Range

By default, MicroCase will display the variable range.  Click on the Settings buttons to change these settings.


Distribution Table

The distribution of your variable will be displayed here.  In the displayed example, the user has stratified by sex.  Therefore, the distribution of the variable LIKE CONG? is displayed separately for males and females.  Using the Codebook Settings box you can change how distribution tables are displayed.


Saving a File

To save your MicroCase data file at any time, click on the Save button on the File & Data Task Menu.


Goto Variable

If you would like to quickly jump to particular variable number, type a number in this box and click on the Goto button.  MicroCase will then display the selected variable number.


Assign Missing Categories

Click on this button to assign categories of the source variable to missing data when the recode is created.


Assigning Missing Data Categories During a Recode

While performing a recode you may wish to assign categories of the source variables to missing data.  MicroCase allows you to assign up to three categories to missing data while creating recoded variables.

To set missing data categories, click on the "Assign Missing Categories" button while performing a recode.  A box will then appear in which you can type up to three category labels in the boxes provided.  Click on the OK button to continue.

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Question Entry (with Grid)

If you choose the question entry (with grid) option, you will enter data into a spreadsheet in which cases are rows and variables are columns.  A box will appear above the spreadsheet that shows the variable name, description and category labels.  Simply click on a category label and MicroCase will insert the correct number for you and move to the next cell.


Question Entry (by Case)

Question entry (by case) also allows you to enter data by clicking on category labels.  In question entry (by case), however, the data grid is hidden from view and the variable description is provided in a larger font.  Entering data using question entry (by case) is quite similar to completing a questionnaire.


Student File Limit

Student versions of MicroCase limit the number of new files that may be created.  If you try to create a new file once this limit has been reached, MicroCase will ask you to delete one of your files.

The box that appears will provide a list of the files you have created.  To delete a file, check the box next to its name and then click on the OK button.

If you want to close this box without deleting one of your files, click on the Cancel button.

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General Introduction

Student ExplorIt and Student MicroCase are student adaptations of the Windows 95 version of the MicroCase Analysis System.  These student software products are designed to accompany workbooks in various areas of the social sciences.

Workbooks which use Student ExplorIt focus on using existing data to answer important social science questions.  Several data sets are included with each workbook and these data sets are typically the most recent, highest quality data available.

Student MicroCase allows the user to create data files, add new data, recode existing data, as well as analyze the data sets provided with the workbook.

A network version of either Student ExplorIt or Student MicroCase is available to instructors who adopt a textbook for use by a class. For more information on network versions of the software, contact support@kdc.com.

Additional information is available at MicroCase’s web site, http://www.microcase.com.

Note:  Some tasks included in the help descriptions may not be available in this student product and some tasks are available only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, visit MicroCase's web site, http://ww.microcase.com, or send email to support@kdc.com.


Introduction to ShowCase

ShowCase Presentational Software (Textbook Edition) is designed for instructors wanting to do live analysis in front of an audience or class. Faculty can augment lectures and stimulate class discussions using the same data sets that are provided with the student book for which it is designed.

ShowCase is similar to Student ExplorIt and Student MicroCase in terms of operation, but all graphic and text screens have been enlarged so that analysis results can easily be read on large monitors or computer-projection systems. ShowCase also includes more statistical procedures than are provided with most student versions.

If you need additional information on ShowCase, consult the Instructor’s Resource Guide for the book you are using. Additional instructions can also be obtained using the on-line Help. For example, if you need help while you are doing an analysis, press the F1 key. An appropriate help screen will appear.

Introduce an exciting new dimension to your lectures with ShowCase Presentational Software. Your classroom will never be the same!


Using the Task Menus

In addition to standard Windows 95 drop-down menus , MicroCase includes a Task Menu system.  The Task Menus group file and data management and statistical tasks together as a series of buttons in the main part of the MicroCase screen.  Each button provides the name and a short description of the task.

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In Student ExplorIt all available tasks are shown on the screen at once.  In Student MicroCase, there are two different Task Menus available—the File & Data Menu, and the Statistics Menu.  To change menus, click on the two buttons on the left-hand side of the Student MicroCase screen:

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In the above example the File & Data menu has been selected.  Note that a white notch will appear next to the selected menu and the color of the menu’s name will change to white.

  File & Data Menu

  Statistics Menu


Sample Task Menu Button

This is the button for the Open task.  You can click on it to open an existing data file.


File & Data Menu

Click here to change to the File & Data Menu.  The File & Data Menu includes such tasks as opening files, defining variables, collapsing and recoding variables, entering data, and generating codebooks.


Statistics Menu

Click here to change to the Statistics Menu.  The Statistics Menu includes such tasks as univariate, correlation, regression, and mapping.


Using the Windows 95 Menus

In addition to the Task Menus, Student MicroCase and Student ExplorIt include standard Windows 95 menus.

To choose a task, click on the menu name.  Choose the task you wish to perform from the drop-down menu that appears.

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Move Up One Level Button

Click here to move up one level in your computer's directory structure.  For example, if you are viewing the contents of the directory "C:\MC4\," then clicking on this button will show you the contents of "C:\."


Look In

Click here to choose the drive and/or directory in which your file is stored.


Create New Folder

Click here to create a new folder/directory.


Show File List

Click here if you only want to view file names.


Show File Details

Click here to show more information about each file in the displayed directory, including the file size, type and date last modified.


File List

A list of files in the current directory will appear here.  Click on the file you want to open.  When you click on a file, information about it will appear in the "Selected File" box.


File Name

When you click on a file, its name will appear in this box.


Files of Type

MicroCase will automatically show only files in MicroCase format.  The full version of MicroCase allows you to import and export other file types.


Open Button

Click here to confirm your choice and open the selected file.


Cancel Button

Click here to close this box without opening a file.


Selected File Information

When you click on a file name you will see information about that file in this box, including a file description (if available), the number of cases in the file and the number of variables.

In the displayed example, the user has clicked on a file named "States," which has 50 cases and 147 variables.  The file is described as "The Fifty States of the U.S."


Special Tasks Available

When you click on a file name, this box will tell you if the selected file supports any of three special tasks--mapping, Auto-Analyzer, and historical trends.  If a task is unavailable, the task name will be dimmed.

In the current example, the user has selected a file named "States."  The Special Tasks Available box indicates that the mapping task will be available with this file.


Show Variable List

Once you have chosen a file, you can click on this button to see a list of all the variables in that file.


File Settings

The File Settings box allows you to view information about the open file--including the file name, file description, weight variable (if any), case name variable (if any), number of cases, number of variables, and missing data categories.

The File Settings box will automatically appear whenever you open a file.  If you wish to view file settings at any other time, click on the “File Settings” button on the File & Data Task Menu .  You can also get to the file settings by clicking on “Settings” from the Windows 95 menu and then choosing “File Settings.”

Once the file settings box has appeared, view or change settings as desired and then click OK.  Click on the screen shot below to learn more about the File Settings box.  For example, click on the File Notes button to see what it does.

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  Setting missing data categories

  Viewing file notes

  Viewing a variable list


File Name

The name of the open data file will appear here.


File Description

If your data file has a description, it will appear here.


Variable List

Click on the Variable List button to view a list of all of the variables in the open data file.


File Information

Information about the open file, including the number of cases and number of variables, will appear here.


File Notes Button

Each MicroCase file ships with notes about the file, which includes such information as the source of variables in the file.  To view the file notes, click on this button.


OK Button

Click the OK button to close the File Settings box.


Convert Labels to Missing Data

If your file includes certain category labels which you do not want to include in analyses, type those category labels into the boxes provided.  MicroCase will automatically remove any category labels you provide here from analyses.

For example, if you do not want the category “NO ANSWER” to be included in statistical analyses, type “NO ANSWER” into one of these boxes.


Weight Variable

In some studies, certain cases are over- or under-sampled.  In this situation, weights must be applied to the cases during analysis to make the results correct for the population which was sampled.  A weight variable contains the weights that should be applied to the cases.  If your file has a weight variable enabled, the name of that variable will appear here.


Case Name Variable

A case name variable is an alphanumeric variable which contains the name of each case.  If your file has a case name variable enabled, the name of that variable will appear here.


Converting Categories to Missing Data

If your data file contains certain categories which you would like to exclude from analyses, MicroCase can automatically convert them to missing data for you.  For example, with survey data, variables may have categories such as “Don’t Know” and “No Answer” which you do not want included in statistical analyses.

To convert category labels to missing data, open the File Settings box.  To do so click on the File Settings button on the File & Data Task Menu .  You can also get to file settings by clicking on “Settings” on the Windows 95 menu and then choosing “File Settings.”

Once the File Settings box appears, type the category descriptions you would like to convert into missing data in the six boxes titled “Convert these labels into missing data.”  Note that these boxes are case sensitive.  In other words, setting the category "No Answer" to missing will have no effect on a category label of "NO ANSWER."  If you want to restore a category label which you previously set to missing data, simply open the File Settings box and erase the desired label.


File Notes

MicroCase data files ship with file notes, which include the sources of variables, suggested citations, and copyright information.

To view the file notes, click on “Settings” on the Windows 95 menu and then choose “File Notes.”  Alternately, you can click on the File Notes button in the File Settings box.  You can also click on the File Notes button on the MicroCase Toolbar to view file notes.

Click on the screen shot below to learn more about the File Notes box.  For example, click on the OK button to see what it does.

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File Name

The name of the open file will appear here.


Slider Bar

Click on the slider bar to scroll through your file notes.


OK Button

Click on the OK button to close the File Notes box.


Cancel Button

Click on the OK button to close the File Notes box.


Check Spelling Button

Click on the Check Spelling button to have MicroCase check the spelling of your file notes.  This option is not available in student versions of MicroCase.


Copy to Clipboard

Click on the Copy to Clipboard button to copy your file notes to the Windows Clipboard.


Print Button

Click on the Print button to print a hard copy of your file notes.


File Notes

The file notes will appear here.


Viewing a Variable List

To view a list of variables in the open file, click on “Settings” on the Windows 95 menu and then choose “Variable List.”  You can also press the F3 key, or click on the Information button on the MicroCase Toolbar to view a list of variables.

Click on the screen shot below to learn more about the Variable List box.  For example, click on the box titled “Variable Description” to see what it does.

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  Click here to learn more about searching the variable list


OK Button

Click on the OK button to close the Variable List box.


Selecting Variables

Some statistical tasks, such as correlation and regression require you to select multiple variables while other tasks, such as univariate and mapping only require you to select one variable.

Whenever you are asked to select variables for a task, a box similar to the one below will appear.  Click on the screen shot below to learn more about selecting variables.  For example, click on “Subset Variables,” to see a description of subsets.

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  Searching for Variables

  Selecting SubsetVariables


Selecting Multiple Variables

Some statistical tasks, such as correlation and regression allow you to select multiple variables.  To select a variable, click on a variable name and then click on the arrow next to “Select Variables.”  You can select multiple variables at once by holding down the left mouse button and dragging the mouse.

To remove a variable from your list of selected variables, select a variable with the left mouse button and then click the right mouse button.  From the menu which appears, choose "Delete."  You can also click on the "Clear All" button to clear all the variables from your selected list.

Whenever you are asked to select variables for a task, a box similar to the one below will appear.  Click on the screen shot below to learn more about selecting variables.  For example, click on “Subset Variables,” to see a description of subsets.

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  Searching for Variables

  Selecting SubsetVariables


List of Selected Variables

The list of variables you have selected will appear here.  In the displayed example, the user has selected five variables—PRES IN 92, WHO IN 88, INTEREST?, IDEOLOGY, INFORMED?

To remove a variable from your list of selected variables, select a variable with the left mouse button and then click the right mouse button.  From the menu which appears, choose "Delete."  You can also click on the "Clear All" button to clear all the variables from your selected list.


Selection Arrow

Once you have clicked on a variable name, click on this arrow to add it to your list of selected variables.


Searching for Variables

Click on the Search button in a variable selection box if you wish to search variable names and descriptions for certain words and/or phrases.  In the box that appears, enter the search words and/or phrases.  The program will then return a list of all those variables which match your search criteria.

In the displayed example (below), the user is searching for variables which include "Clinton."  In this case, MicroCase would return a list of those variables which contain "Clinton" in the variable name, variable description, and/or category labels.

Click on the screen shot below to learn more about searching for variables.  For example, click on the OK button to see what it does.

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Selecting Subsets

If you are interested in only one category of respondents, then you might choose to select a subset of cases.  For example, if you only want to see the distribution of a variable for females, you can use sex as a Subset Variable.

You can also create subsets using multiple variables.  For example, you could subset by race and by gender if you only wanted to use black females in an analysis.

When you select a Subset Variable, a box will appear in which you choose which categories to include or exclude from the analysis.  Click on the screen shot below to learn more about choosing subset variables.  For example, click on the OK button to see what it does.

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Note: To modify a subset, right-click on the subset variable with your mouse.


Statistics Menu

You can access Statistics tasks in two ways.  First, you can choose the Statistics Task Menu and then select the task of interest.  Alternately, you can click on the “Basic” menu on the Windows 95 menu bar and then click on a task.

Whether a particular statistical task will be available depends upon the open data file.  Not all statistical tasks are available with all files.  Click on a button below to learn more about a particular statistical task:

  Univariate

  Cross-Tabs

  t-Test

  Analysis of Variance (ANOVA)

  Auto-Analyzer

  Mapping

  Scatterplot

  Correlation

  Regression

  Historical Trends


Introduction to Univariate

The univariate task shows the distribution of a single variable at any level of measurement.

Once you choose the Univariate task, a box will then appear which allows you to select a variable for univariate and a subset variable, if necessary.

Once you have selected a variable, either a pie graph or frequency table will appear, depending on the type of variable used.

Note:  The Univariate task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to see the graphs and statistics available for Univariate


Pie Graph

A pie graph displays a frequency distribution as a circle (or pie shape)  with each category shown as a different colored "slice."  The larger the slice the greater the number of cases which fall into that category.

Click on the screen shot below to learn more about pie graphs.  For example, click on the colored pie to see a description.

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Pie Graph

The pie graph appears here.  Each category is given a different colored slice.  In the displayed example, the blue slice represents respondents who watched the network news  0-2 days in the past week.


Variable Name and Description

The variable's name and description will appear here.  The current example shows a variable named "WATCH NEWS."


Category Labels

The categories of your variable will appear here.  The displayed example shows  a variable with three categories.  The box next to each category shows the color of its pie slice.


Bar Graph

A bar graph is a diagram of a univariate distribution in which a vertical box represents the frequency of each category.  The height of each box is determined by the relative frequency of the category.

Click on the screen shot below to learn more about bar graphs.  For example, click on the red arrow beneath the first bar to see what it does.

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Bars

Each bar represents one category of your variable.  The height of each bar represents the number of cases in that category.


Selected Bar

Click on a bar to see the category label, and the number and percent of cases in that category.  Note that a red arrow will appear below the selected bar.

In the current example, the first category of the variable, “WATCH NEWS,” is “0-2 DAYS.”  736 cases or 43.0% of the sample fall into this category.


Cumulative Bar Graph

A cumulative bar graph is a diagram of a univariate distribution in which a vertical box represents the cumulative percentage of each category.  The height of each box is determined by the cumulative percentage of the category.

Click on the screen shot below to learn more about bar graphs.  For example, click on the red arrow beneath the second bar to see what it does.

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Cumulative Bars

Each bar represents one category of your variable.  The height of each bar represents the cumulative percentage.


Selected Bar

Click on a bar to see the category label, number of cases in that category and the cumulative percentage.  Note that a red arrow will appear below the selected bar.

In the current example, the second category of the variable, “WATCH NEWS,” is “3-6 DAYS.”  471 cases fall into this category.  Over 70% of the sample fall in category two and the category below it.


Univariate Summary Statistics

When you choose to view summary statistics a frequency table and a number of statistics will appear.

Click on the screen shot below to learn more about univariate summary statistics.  For example, click on “Mean” to see the definition of a mean.

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Introduction to Cross-tabulation

The Cross-Tabulation task allows you to examine the joint distribution of two or more categorical variables.  The variables are typically either nominal or ordinal ; certain ratio variables may also be categorical.  The resulting table may be percentaged by row, by column, or by the total.  Expected frequencies and chi-square results may be shown.  Measures of association for nominal and ordinal variables can be examined.  Analysis may be restricted to a subset of cases and control variables may be used.

This task is especially useful for examining the effect of one nominal variable on another.  For example, you might examine the effect of gender on political party preference or the effect of religious affiliation on attitude toward capital punishment.

Once you have selected the Cross-tabulation task, a box will then appear which allows you to select a row variable and a column variable .  You may also select subset variables and control variables, if desired.  Click here if you need help on selecting variables .

Once you have selected your variables, a frequency table between the row and column variable will appear.  If you have selected control variables, a frequency table between the row and column variable for the first combination of categories of the control variables is shown.

Note:  The Cross-tabulation task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to see the tables, statistics, and graphs available with Cross-tabulation

  Click here to learn about using control variables with Cross-tabulation

  Click here to learn how to collapse variables in Cross-tabulation


Cross-tabulation Display Options

Once you have selected your variables, a frequency table between the row and column variable will appear.  If you have selected control variables, a frequency table between the row and column variable for the first combination of categories of the control variables is shown.

On the left hand side of your screen will be several cross-tabulation display options.  Using these display options you can view different percentages (row, column and total), expected frequencies , summary statistics, and a stacked bar graph .  Click on the screen shot below to learn more about the display options available.  For example, click on “Bar Stack”  to see a description of stacked bar graphs.

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To learn more about specific cross-tabulation display options and to see examples, click below:

  Cross-tabulation frequency tables

  Column percentages

  Row percentages

  Total percentages

  Expected frequencies

  Cross-tabulation summary statistics

  Stacked bar graphs

  See also


Cross-tabulation Frequency Table

 Click here to see a frequency table between the row and column variables.


Column Percentages

Click here to view column percentages.


Row Percentages

Click here to view row percentages.


Total Percentages

Click here to view the total percentages.


Expected Frequencies

Click here to view expected frequencies.  The expected frequency is the number of cases in a cell that would be expected if the two variables were unrelated.


Cross-tabulation Summary Statistics

Click here to view cross-tabulation summary statistics, including chi-square, lambda, and gamma.


Stacked Bar Graph

Click here to view a stacked bar graph.  A stacked bar graph is a diagram of the cumulative distribution of each category of the row variable across each category of the column variable.


Cross-tabulation Frequency Table

The cross-tabulation frequency table shows the number of cases in each combination of your row and column variables.  The example below shows a cross-tabulation of political party by sex.  In this example, 350 of the respondents were male democrats and 627 were female democrats.

Click on the screen shot below for more information.  For example, click on the row labeled “Missing” to see a description of its contents.

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Variable Names

The names of your variables will appear here in the following format: ROW by COLUMN.  In the current example, POL.PARTY is the row variable and SEX the column variable.


Row Variable Categories

The categories of the row variable will appear as rows in your table.  In the current example, the row variable, POL. PARTY, has three categories—Democrat, Independ., and Republican.


Column Variable Categories

The categories of the column variable will appear as columns in your table.  In the current example, the column variable, SEX, has two categories—Male and Female.


Row Totals

This column shows the total of each row of your table.


Row Totals

This column shows the total number of cases in each row of your table.  In row percentaging, the percent shown will always be 100.


Column Totals

This row shows the total number of cases in each column of your table.  In column percentaging, the percent shown will always be 100.


Column totals

This row shows the total of each column of your table.


Missing Data

This row shows the number of missing cases at each level of the column variable.


Table Cells

Each cell of your table shows the number of cases which fall in each combination of your row and column variables.


Grand Total

The total number of cases in the table will appear here.


Column Percentages

To percentage cases down each column, choose column percentages.  The example below shows a cross-tabulation of political party by gender.  In this example, 27.7% of males are Democrats, 40.7% independent, and 31.6% are Republican.

Click on the screen shot below for more information.  For example, click on the row labeled “Missing” to see a description of its contents.

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Table Cells

Each cell of your table shows the number of cases and percentage of cases (in the column) which fall in each combination of your row and column variables.


Row Totals

This column shows the total number of cases and percentage of cases in each row of your table.


Column Totals

This column shows the total number of cases and percentage of cases in each column of your table.


Row Percentages

To percentage cases across each row, choose row percentages.  The example below shows a cross-tabulation of political party by gender.  In this example, 35.8% of males and 64.2% of females are Democrats.

Click on the screen shot below for more information.  For example, click on the row labeled “Missing” to see a description of its contents.

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Table Cells

Each cell of your table shows the number of cases and percentage of cases (in the row) which fall in each combination of your row and column variables.


Table Cells

Each cell of your table shows the number of cases and percentage of cases which fall in each combination of your row and column variables.  Note that when you are using a control variable, the number of cases in a cell represents the number of cases in the current level of the control variable which fall into that combination.


Total Percentages

To show the percentage of the total number of cases in each cell, choose total percentages.  The example below shows a cross-tabulation of political party by gender.  In this example, 12.3% of the total sample are male democrats and 28.3% of the total sample are Republicans.

Click on the screen shot below for more information.  For example, click on the row labeled “Missing” to see a description of its contents.

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Table Cells

Each cell of your table shows the number of cases and percentage of cases (of the total) which fall in each combination of your row and column variables.


Expected Frequencies

The expected frequency is the number of cases in a cell that would be expected if the two variables were unrelated.  The chi-square statistic tells you if the observed frequencies of your variable are significantly different from these expected frequencies.  Therefore, when you choose to view expected frequencies, MicroCase will also provide the chi-square statistic.

Click on the screen shot below for more information.  For example, click on the row labeled “Missing” to see a description of its contents.

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Table Cells

Each cell of your table shows the number of cases and expected frequency for each combination of your row and column variables.


Cross-tab Summary Statistics
Cross-tabulation Summary Statistics

When you choose to view cross-tabulation summary statistics a number of nominal and ordinal statistics will appear.   When you use a control variable, the summary statistics screen will show you the value of partial gamma.

Click on the screen shot below to learn more about these summary statistics.  For example, click on “Gamma” to see the definition of gamma.

Note: the probability provided with the ordinal statistics applies to all of the ordinal statistics.

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Stacked Bar Graph

The stacked bar graph provides you with a visual representation of the relative percentages of each level of the row variables within each level of the column variable.  Each bar will total 100%.  In the displayed example, the stacked bar graph shows that the percent Democrat is higher for females than for males.

Click on the screen shot below to learn more about the stacked bar graph.  For example, click on the bars to see a description.

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Using Control Variables in Cross-tabulation

If you have selected control variables for your cross-tabulation table, the first table displayed will be a frequency table between the row and column variable for the first combination of categories of the control variables.

In the displayed example, the user is doing a cross-tabulation table with POL. PARTY (political party) as the row variable and SEX (gender) as the column variable .  The analysis includes a control variable, R.FUND/LIB (the fundamentalism/liberalism of the respondent's religion), with three categories—fundamentalist, moderate, and liberal.  Therefore, MicroCase will display four tables—one for each level of the control variable plus one for cases with missing data on the control variable.

The screen shot below shows the cross-tabuation table for POL. PARTY by SEX, controlling for R.FUND/LIB.  This is the first table displayed and, therefore, shows the table for respondent’s who are fundamentalist.   Click on the screen shot for more detailed information.  For example, click on the cells of the table to see a description.

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Note that when you use a control variable, the summary statistics screen will also show you the value of partial gamma.

When you use a control variable, two arrows will appear underneath the Cross-tabulation display menu.  Click on the arrows to step backwards and forwards through the levels of your control variables.  Click on the screen shot below for more detailed information.

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When you use a control variable in cross-tabulation, the summary statistics screen will also provide the value of partial gamma.

  See also


Collapsing Variables in Cross-tabulation

The cross-tabulation task allows you to temporarily collapse categories of your row variable or column variable or convert categories to missing data .  The cross-tabulation collapse feature does not permanently change your variable.  Any changes you make only last as long as you are viewing your cross-tabulation tables.

To collapse a variable, click on the category label(s) you would like to collapse or convert to missing data and then click on the Collapse button on the left hand side of the screen.  A box will appear to confirm your choice and provide a name for your new, collapse category, if necessary.  Once you have made your choices, MicroCase will provide a new table.

  Click here to see a detailed example

  See also


Cross-tabulation Variable Collapse, Step 1

The first step in collapsing categories or converting categories to missing data in cross-tabulation is to select the categories you wish to collapse/convert.  To select categories, click on the category labels in your cross-tabulation table.  When you click on a category label its row or column will be highlighted in green (rows) or blue (columns).

The following example shows a cross-tabulation table with a row variable named REL IMP? and a column variable which indicates the respondent's region of the country (REGION).   REL IMP? is a variable which asked respondents whether or not religion is an important part of their lives.  REGION indicates whether respondents are from the North Eastern, North Central, Southern, or Western region of the United States.

If you wanted to temporarily collapse the REGION variable so that you could compare Western respondents with everybody else (i.e. put North East, North Central, and the South together),  the first step would be to click on those three categories in the table.  Click on the screen shot below for more information.  For example, click on the blue, highlighted  columns for a description.

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  Click here for step 2


Cross-tabulation Variable Collapse, Step 2

Once you have selected the rows or columns you would like to collapse or convert to missing data, click on the Collapse button to the left of your table.

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Once you click on the Collapse button, a box will appear which allows you to choose what to do with the selected rows or columns.  If you want to collapse the selected rows/columns together into a single category, choose “Create New Collapsed Category.”   To convert the select rows/columns to missing data, choose “Convert to Missing Data (Drop).”  If you have chosen to create a new collapsed category, you can provide a name for the new category.  Once you click on “OK,” your table will appear with the desired changes.

Click on the screen shot below for more information.  For example, click on the OK button to see what it does.  In the displayed example, the user is collapsing the categories NORTHEAST, N.CENTRAL, and SOUTH into a single category, which will be called “OTHER”.

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  Click here for step 3


Cross-tabulation Variable Collapse, Step 3

After selecting your collapse options, your table will appear with the desired changes.  In the displayed example, the NORTHEAST, N.CENTRAL and SOUTH categories have been combined into a new category named “OTHER”.

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Introduction to Mapping

The mapping task shows a graph of each case’s value on an area map.  Each geographic unit is given a color based on its value on the variable of interest.  Higher values are given darker shades.  This type of graph is quite useful for geographic analysis.

Once you have chosen the Mapping task, a box will then appear which allows you to select a variable for mapping, an optional second variable and/or subset variable, if necessary.

If you have selected one variable then a single map will appear.  If you have selected two variables, then two smaller maps will appear—one for each variable.

Note:  The Mapping task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Mapping Display Options

  Comparing Maps


Why Can't I Map with My File?

The mapping task will only be available for files that have a MicroCase map attached.  When you open a file, MicroCase informs you if the file has an attached map.


Mapping Display Options

Once you have selected your variable(s), either a single map or two maps will appear, depending on whether you have chosen one or two variables.

On the left hand side of your screen will be several map display options.  Using these display options you can view shaded maps, spot maps, ranked lists, alphabetical lists and legends.  Click on the screen shot below to learn more about the display options available.  For example, click on “Spot Fill” to see a description of Spot Fill maps.

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To learn more about specific map options, click below:

  Click here to see a standard  map

  Click here to learn about Rank and Alpha Lists

  Click here to see a Spot Fill map

  Click here to see a map legend

  Click here to learn about finding cases

  Click here to learn about comparing maps


Map

Click here to view, or return to, your map.


List Rank

Click here to view a ranked list of cases.


List Alpha

Click here to view an alphabetized list of cases.


Spot Fill

Click here to view a map in which a spot represents the value of each case.  The larger the spot, the higher the values on the variable of interest.


Legend

In order to map your variable, MicroCase automatically collapses it into a small number of categories.  To see the range of values included in each category, click on “Legend.”


Find Case

If you are having trouble finding a case, click here.  A list of all the cases on the current map will appear.  Choose the case you wish to view and MicroCase will highlight it for you.


Standard Map

After you have selected your mapping variable, a map will appear.   Each case will be given a color based on its value on the variable of interest.  Darker colors equal higher values.

Click on the screen shot below to learn more about maps.  For example, click on the highlighted state (Wyoming) to see more about selecting geographical units.

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Selected Unit

If you click on a geographic unit, it will be highlighted in green.  The name of the case, value on the selected variable, and rank will also appear below the map.  In the current example, Wyoming has been selected.


Map Units

Each geographical unit on your map will be given a color based on its value on the selected variable.  Darker colors equal higher values.


Information on the Selected Unit

If you click on a geographical unit, information about that unit will appear here.  In the current example the user has selected Wyoming, which has a value of 2.04 on the variable “FED HIWAY$”.  This gives Wyoming an overall ranking of ninth.


Variable Name and Description

The name and description of the selected variable will appear here.  In the current example, the user is mapping a variable named “FED HIWAY$.”


Spot Fill Maps

A spot map shows the value of each case on the variable of interest as a colored spot.  The larger the spot the higher the value.

Click on the screen shot below to learn more about spot fill maps. For example, click on the highlighted state (Wyoming) to see more about selecting geographical units.

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Map Units

Each geographical unit on your map will be given a colored spot based on its value on the selected variable.  The larger the spot, the higher its value.


Selected Unit

If you click on a geographic unit, its spot will be highlighted in green.  The name of the case, value on the selected variable, and rank will also appear below the map.  In the current example, Wyoming has been selected.


Ranked and Alphabetical Lists

If you wish to view a list of all the cases on your map, there are two different types available—rank and alpha.  Rank lists provide a list of cases in rank order.  An alpha list shows you an alphabetical list of cases.

To view a ranked list, choose “List: Rank.”  To view an alphabetical list, choose “List: Alpha.”

Click on the screen shot below to learn more about ranked lists.  For example, click on “Rank” to see a description of case rankings.

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Map Color

The color of each case on the map will appear here.


Rank

Each case’s ranking on the variable of interest will appear here.


Case Name

The name of each case will appear here.


Case Value

 The value of each case on the mapped variable will appear here.


Slider Bar

Click on this slider bar to scroll through the list of cases.


Map Legend

In order to map your variable, MicroCase automatically collapses it into a small number of categories.  To see the range of values included in each category, click on “Legend.”  A legend will then appear in the bottom, right-hand corner of your map.

Click on the screen shot below to learn more about map legends.  For example, click on the column labeled “N” to see a description of its contents.

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Category Color

The color of each category as displayed on the map will appear here.


Value Range

The values included within each mapping category will appear here.  In the displayed example, the first category (light orange) contains cases with values from 0.83 to 1.00.


Number of Cases (N)

The number of cases in each mapping category will appear here.  In the displayed example, the first category (light orange) has 8 cases.


Missing Cases

The color which will be used for displaying missing cases will appear here.


Finding Cases

If you are having trouble finding a case, click on “Find Case.”  A box will then appear with a list of all the cases on your map.

Select the case you want to find by clicking on it.  Click OK and MicroCase will highlight the selected case on your map.  See the screen shot below to learn more about finding cases.  For example, click on the OK button to see what it does.

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Case Names

A list of all the cases on your map will appear here.  To find a case, click on its name.  A check mark will appear next to the selected case name.

In the displayed example the user has selected “NORTH CAROLINA.”


OK Button

Click on the OK button to return to your map.  MicroCase will highlight the case you selected.


Cancel Button

Click on the Cancel button to return to your map without highlighting a case.


Comparing Maps

If you select two variables for mapping, MicroCase will display a map for each variable, so that you may compare them.  When you click on a geographic unit on either map, that unit will be highlighted on both maps.  Information on the selected unit will appear to the right of each map.

For each map, separately, you can choose to view either a standard map or a ranked or alphabetic list.  If you choose Spot Map , Legend , or Find Case , the results will be applied to both maps.

Click on the screen shot below for more information on comparing maps.  For example, click on the correlation coefficient (r=-0.625) to see a description.

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First Variable Name and Description

The name and description for variable 1 will appear here.


Second Variable Name and Description

The name and description for variable 2 will appear here.


Correlation

When comparing maps, the correlation between the two variables will appear here.


Information on the Selected Unit

When you click on a geographic unit on either map, the name of the selected case and value on the variable of interest will appear next to each map.

In the displayed example, the user has clicked on Wyoming.  Wyoming has a rank of 39 on the variable “SAME HSE90" and a rank of 2 on the variable “SUICIDE 93.”


Selected Unit

When you click on a geographic unit on either map it will be highlighted in green on both maps. Information about the selected unit will appear next to each map.

In the current example, the user has selected Wyoming.


Introduction to Scatterplots

The Scatterplot task allows you to explore the joint distribution of two ordinal or ratio variables.  The x-axis represents the independent variable and the y-axis represents the dependent variable .  Each dot represents the intersection point of the values on these variables for a particular case.  For example, with this task you could visually inspect the relationship between educational attainment and income.

There are several options available with the Scatterplot task.  The regression line may be shown on the scatterplot.  The residuals may also be shown.  Outliers can be identified and removed.  The location of any case can be found with the Find case option.  Analysis may also be limited to a subset of cases.

Once you select the Scatterplot task, a box will appear which allows you to select the independent and dependent variables.  You may also select subset variables, if desired.  Click here if you need help on selecting variables.

Once you have selected your variables, a scatterplot will appear.  The example below shows a scatterplot between two variables—ALCOHOL and MARRIAGE.  Click on the screen shot for more information.  For example, click on the correlation coefficient (r) to see a definition.

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Note:  The Scatterplot task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to learn about regression lines and residuals

  Click here to learn about finding cases and outliers


Scatterplot Display Options

Once your scatterplot has appeared, you can view the regression line and residuals.  To show the regression line or residuals, click on the menu which will appear to the left of your scatterplot.  Click on “Reg. Line” to turn the regression line display on and off.  Click on “Residuals” to turn the display of residuals on and off.

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  Click here to see a sample regression line

  Click here to see a sample residual display


Regression Line

The regression equation describes the line (or plane) that best predicts the values of the dependent variable from the values of the independent variable.  When you turn on the regression line, it will be displayed as a green line in your scatterplot.  The regression equation will appear below your scatterplot.

The example below shows a scatterplot for ALCOHOL and MARRIAGE with the regression line displayed.  Click on the screen shot for more information.  For example, click on the regression equation for a description.

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Residuals

The residual is the difference between the observed value of a variable and the value predicted using least squares regression with one or more independent variables.  When you turn on the display of residuals, purple lines will show the distance between each case and the regression line.

The example below shows a scatterplot for ALCOHOL and MARRIAGE with the regression line and residuals displayed.  Click on the screen shot for more information.  For example, click on the regression equation for a description.

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Finding Cases and Outliers

Once your scatterplot has appeared, you can highlight cases using the Find Case option and highlight outliers using the Find Outlier option.  Once you have highlighted an outlier, you can also choose to remove it. To find cases and outliers, click on the menu which will appear to the left of your scatterplot.  Click on “Case” to find a case.  Click on “Outlier” to find outliers.  Click on the Remove button to remove selected cases and outliers from the scatterplot.

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  Click here to learn more about finding cases

  Click here to learn more about finding and removing outliers

  See also


Finding Cases

To highlight a case in your scatterplot, click on “Case.”  A box will then appear with a list of all the cases in your data file.

Select the case you want to find by clicking on it.  Click OK and MicroCase will highlight the selected case in your scatterplot.  Click on the screen shot below to learn more about finding cases.  For example, click on the OK button to see what it does.

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MicroCase will highlight the selected case by placing a red box around it.  Information about the selected case will appear to the left of the scatterplot--including its name, value on the independent and dependent variable, and the value of the correlation coefficient (r) if the case were removed.  The example below shows a scatterplot for ALCOHOL and MARRIAGE.  Click on the screen shot below for more information.  For example, click on the correlation coefficient (r) to see a definition.

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Once you have selected a case, you can click on the Remove button if you wish to remove it from your scatterplot. MicroCase will remove the case and redraw your scatterplot.

  See also


Finding Outliers

To highlight the most deviant case, or outlier, in your scatterplot, click on “Outlier.”  MicroCase will highlight the most deviant case by drawing a red box around it. Information about the selected case will appear to the left of the scatterplot--including its name, value on the independent and dependent variable, and the value of the correlation coefficient (r) if the outlier were removed.

If you wish to remove the outlier, click on the Remove button.  MicroCase will remove the outlier and redraw your scatterplot.  You can then click on “Outlier” again if you wish to view the next most deviant case.

The example below shows a scatterplot of ALCOHOL and MARRIAGE with an outlier selected.   Click on the screen shot below for more information.  For example, click on the correlation coefficient (r) to see a definition.

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Introduction to Correlation

The correlation coefficient is a measure of association which summarizes the extent to which the relationship between two ordinal or ratio variables is linear.  The correlation task allows you to examine a set of correlations.  For example, you could examine the correlations among a set of variables, such as educational attainment, occupational prestige, father’s educational attainment, and income.

You can choose from pairwise and listwise deletion of missing data and from one and two-tailed tests of significance .  When listwise deletion is used, Cronbach’s Alpha will be automatically computed for you.  Analysis may also be limited to a subset of cases.

Once you select the Correlation task, a box will appear which allows you to select variables.  You may also select subset variables, if desired.  Click here for help with selecting variables.

Once you have selected your variables, the correlation matrix will appear.

Note:  The Correlation task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to see the options available with the Correlation task


Correlation Display Options

Once you have chosen your variables, a correlation matrix will appear.  To choose between pairwise and listwise deletion of missing data and between one-tailed and two-tailed tests of significance, click on the menu to the left of your correlation matrix.

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  Click here to see an example of pairwise deletion

  Click here to see an example of listwise deletion


Pairwise Deletion

In pairwise deletion, a case with missing data is omitted only from the calculations directly involving the variable(s) with missing data; the case is included in calculations in which these variables are not directly involved.

The following example shows a correlation matrix which uses pairwise deletion for three variables—PLAYBOY, ALCOHOL and MALE HOMEB.  Click on the screen shot below for more information.  For example, click on “N” to see a definition.

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Listwise Deletion

In listwise deletion of missing data, a case containing missing data will be omitted from all calculations.

The following example shows a correlation matrix which uses listwise deletion for three variables—PLAYBOY, ALCOHOL and MALE HOMEB.  Click on the screen shot below for more information.  For example, click on “Cronbach’s Alpha” to see a definition.

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Introduction to Regression

Regression allows you to examine the linear effect of one or more independent variables on a dependent variable .  The dependent variable should be either ordinal or ratio ; the independent variables may be ordinal or ratio variables.  Nominal variables may be used as independent variables if they have been converted to dummy variables .

Using regression analysis you can determine the linear effect of an independent variable when the effects of the other independent variables have been removed.  You can also assess the combined effect of a set of independent variables on a dependent variable.  For example, you could see if educational attainment affects income when occupational prestige is controlled; you could also assess how much variation in income could be explained by the combination of educational attainment and prestige.

There are several different options available with the regression task.  You may view a graphical representation of the regression equation, ANOVA statistics, variable means and a correlation matrix.  You can also perform your analysis on a subset of cases, if desired.

Once you select the Regression task, a box will appear which allows you to select your independent and dependent variables.  You may also select subset variables, if desired.  Click here for help with selecting variables.

Once you have chosen your variables, one of two screens will appear.  If there are eight or fewer independent variables, the first screen to appear will be a graphic showing the standardized beta coefficients , the bivariate correlation coefficients , and the multiple R-squared.  If there are more than eight independent variables, the ANOVA screen will be shown.

Note:  The Regression task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to see the different display options available with regression


Regression Display Options

Once you have chosen your independent and dependent variables, one of two screens will appear.  If there are eight or fewer independent variables, the first screen to appear will be a graphic showing the standardized beta coefficients , the bivariate correlation coefficients , and the multiple R-squared.  If there are more than eight independent variables, the ANOVA screen will be shown.

There are four different displays available with the Regression task. You can view the graphical representation of the regression equation, the ANOVA statistics, a correlation matrix, and the variable means.

In addition to the four available displays, you may also choose between listwise or pairwise deletion , and between one-tailed and two-tailed tests of significance.

To switch between these different displays, click on the menu which will appear to the left of your regression results.

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  Click here to see the regression graph

  Click here to see the ANOVA statistics

  Click here to see the correlation matrix

  Click here to see the variable means


Regression Graph

The regression graph provides a visual display of your regression equation.  Your independent variables will appear on the right side of the screen with lines connecting them to the dependent variable.  The standardized beta coefficient and correlation coefficient will be presented for each independent variable.  The multiple R-squared will appear in the upper right hand corner.

The example below shows the regression of BURGLARY on three independent variables—CHURCH MEM, MALE HOMES, and % POOR.  As the graph shows, only % POOR had a significant effect upon BURGLARY.  The multiple R-squared of 0.172 tells us that the independent variables account for 17.2% of the variance in BURGLARY.

Click on the screen shot below for more information.  For example, click on the multiple R-squared for a definition.

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Analysis of Variance Statistics

The Analysis of Variance statistical procedure partitions the total variation (sum of squares) of the dependent variable.  The nature of this partitioning depends on the particular task, but the underlying idea is to compare the variation accounted for or caused by the independent variable(s) with the error (or residual) variation.  The total sum of squares is the variation of the dependent variable.  The regression sum of squares is the variation explained by the regression equation.  The residual sum of squares (or error sum of squares) is the variation unexplained b the regression equation.

The ANOVA statistics shows the values of the regression coefficients, both standardized and unstandardized .  The standard error of each unstandardized coefficient is shown, as well as its statistical significance.  The partitioning of the sum of squares into regression sum of squares and residual sum of squares is also shown.

The following example shows the ANOVA statistics for a regression of BURGLARY on three independent variables—CHURCH MEM, MALE HOMES, and % POOR.  Click on the screen shot below for more information.  For example, click on multiple R-squared for a definition.

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Correlation Matrix

The correlation coefficient is a measure of association which summarizes the extent to which the relationship between two ordinal or ratio variables is linear.  The correlation matrix shows the correlations between all of the variables in your regression equation.

The following example shows the correlation matrix for four variables—BURGLARY, CHURCH MEM, MALE HOMES, and % POOR.  Click on the screen shot below for more information.  For example, click on Cronbach’s Alpha for a definition.

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Means

To see the means, standard deviations, and number of cases (n) for each of your variables, choose “Means” from the regression display menu.

The following example shows the means, standard deviations and number of cases for four variables—BURGLARY, CHURCH MEM, MALE HOMES, and % POOR.  Click on the screen shot below for more information.  For example, click on the mean column for a definition.

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  See also


Introduction to Test of Means (t-Test and ANOVA)

The t-Test and ANOVA tasks are both used to test whether the values of an ordinal or ratio variable vary across the levels of a nominal or categorical variable.  Use the t-Test when the independent variable has only two categories.  The ANOVA task is used when the independent variable has more than two categories.

You could use a test of means to examine the effect of one variable on another.  For example, you could look at the effect at race on income using ANOVA, or the effect of sex on income using a t-Test.

Note:  The ANOVA and t-Test tasks are not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to learn more about the t-Test

  Click here to learn more about ANOVA


t-Test

Use the t-Test to test for a significant difference in means in a ratio or ordinal dependent variable across the levels of a categorical independent variable with two categories.  For example, you could use the t-Test to see if men and women have a significant difference in their mean levels of occupational prestige, or test for a significant difference between liberals and conservatives in church attendance.

If your independent variable has more than two categories, then you should use the ANOVA task to test for a significant difference in means on a dependent variable.

Once you select the t-Test task, a box will appear which allows you to select your independent and dependent variables.  You may also select subset variables, if desired.  Click here if you need help on selecting variables.

  Click here to see the different displays available with the t-Test


ANOVA

Use ANOVA to test for significant differences in means in a ratio or ordinal dependent variable across the levels of a categorical independent variable with more than two categories.  For example, you could use ANOVA to see if liberals, conservatives and moderates have significant differences in their mean levels of occupational prestige, or test for a significant difference between Catholics, Protestants, and Jews in church attendance.

Once you select the ANOVA task, a box will appear which allows you to select your independent and dependent variables.  You may also select subset variables, if desired.  Click here if you need help on selecting variables.

  Click here to see the different displays available with ANOVA


Test of Means Display Options

Once you have chosen your independent and dependent variables, a graphical display of your t-Test or ANOVA results will appear first.  This graphical display is, in fact, a box-and-whisker diagram .

There are three different displays available with the t-Test and ANOVA tasks. You can view the box-and-whisker diagram, the ANOVA statistics, and the variable means.  To switch between these three different displays, click on the menu which will appear to the left of your t-Test and ANOVA results.

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  Click here to learn more about the t-Test and ANOVA graph

  Click here to learn more about the ANOVA statistics

  Click here to learn more about the variable means

  Click here to learn about finding and removing cases


ANOVA/t-Test Graph

Once you have chosen your independent and dependent variables for the t-Test or ANOVA task, a box-and-whisker diagram will appear.

The independent variable will be shown on the x-axis (horizontal) and the dependent variable is shown on the y-axis (vertical).  The leftmost column of dots represents the values of the dependent variable within the first category of the dependent variable, the next column, the values within the second category, and so on.  The boxes represent one standard deviation above and below the mean for the dependent variable within that particular category; the dots and the box represent the distribution within each category of the independent variable.

A line connects the mean of the dependent variable across categories of the independent variable.  If this line were flat, this would indicate no differences in the mean of the dependent variable across categories of the independent variable.

The example below shows a box-and-whisker diagram for a t-Test of LK CLINTON (how much the respondent likes Bill Clinton) by SEX.  As the diagram shows, females had a higher mean on LK CLINTON than males.  Click on the screen shot below for more information.  For example, click on the overall mean for a description.

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  See also


Analysis of Variance Statistics

The Analysis of Variance statistical procedure partitions the total variation (sum of squares) of the dependent variable.  The nature of this partitioning depends on the particular task, but the underlying idea is to compare the variation accounted for (or "caused") by the independent variable(s) with the error (or residual) variation.  The total sum of squares is the variation of the dependent variable.  The between sum of squares is the variation explained by the independent variable.  The within sum of squares (or error sum of squares) is the variation unexplained by the independent variable.

The example below shows the ANOVA statistics for an ANOVA of LK CLINTON by RACE2.  As the F statistic shows, there were statistically significant differences in the mean of LK CLINTON across categories of RACE2.  Click on the screen shot below for more information.  For example, click on Eta squared for a definition.

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  See also


Means

The means display option shows the mean, standard deviation, and number of cases (n) on the dependent variable for each category of the independent variable.  This display will also tell you whether the difference in means across groups is significant.

The example below shows the mean of a variable, LK CLINTON, across the categories of an independent variable, SEX.  As the display tells us, there is a significant difference in the mean of LK CLINTON across the categories of SEX.  Click on the screen shot below for more information.  For example, click on the standard deviation for a definition.

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  See also


Introduction to Auto-Analyzer

The Auto-Analyzer task is a powerful analysis tool that utilizes artificial intelligence to help you obtain statistics and “factoids” on hundreds of topics.  After selecting a survey question for analysis, Auto-Analyzer provides tables and summaries of the results.

To use the Auto-Analyzer, click on the Auto-Analyzer button.   A box will then appear which allows you to select a variable for analysis.

Once you have selected a variable, a univariate frequency distribution will appear which shows the distribution of the variable for all respondents.  The example below shows the initial Auto-Analyzer results for a variable named PRES 92—who the respondent voted for in the 1992 presidential election.  As the results show, 47.8% of the respondents said they had voted for Clinton in the 1992 presidential election.

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To the left of your analyzer results will be a menu allowing you to choose from key demographic variables (i.e. gender, race, political party, age, income, etc.).  After choosing one of these demographic views, a table appears in which the survey question is “cross-tabulated” with the chosen demographic variable.

Note:  The Auto-Analyzer task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to learn more about the demographic views


Demographic Views

Using the menu to the left of your analyzer results, you can choose key demographic variables (i.e. gender, race, political party, age, income, etc.)  After choosing one of these demographic views, a table appears in which the survey question is “cross-tabulated” with the chosen demographic variable.

To switch between demographic views, click on the desired demographic on the left hand side of your screen.  For example, click on “sex” to see your variable broken down by gender.  Click on “Univariate” to see the frequency distribution for the entire sample.  Click on “Summary” to see the results summarized for all of the available demographic groups.

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Once you have chosen a demographic variable, a crosstab table will appear.  For example, if you choose the Race variable, a crosstab of Race by your dependent variable would then appear.

Below the tabulated results, several plain-English sentences provide a clear, succinct description of the table. This interpretation is generated using artificial intelligence. Not only are you provided with a basic description of the results, but you are given information on the strength of the relationship (if any) and told whether the findings are statistically significant Depending on the results, an additional explanation is provided in which the direction of the relationship is described (e.g., it increases with age; it decreases as income increases) even curvilinear relationships  are explained.

  Click here to see an example of a demographic view in Auto-Analyzer


Demographic View Example

The following example shows the Auto-analysis results for the variable PRES 92 (who the respondent voted for in the 1992 presidential election) by Race.  The top of the screen shows a crosstab table of RACE by PRES 92. Below the tabulated results, several plain-English sentences provide a clear, succinct description of the table.

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Why Can't I Use Auto-Analyzer with My File?

The Auto-Analyzer task requires a specially prepared data file.  Therefore, not all data files support the Auto-Analyzer task.   When you open a file, Student ExplorIt informs you if the Auto-Analyzer task will be available.


Introduction to Historical Trends

The Historical Trends task allows you to show changes in a variable or variables over time.  Variables are displayed as lines across a graph of years, providing an excellent visual display of any upward or downward trends.  Furthermore, the Historical Trends display includes a list of important historical events.  When you click on an event, a line appears on the trend graph, allowing you to examine how that event may have affected your variables of interest.

To show historical trends, click on the Historical Trends button.  A box will then appear which allows you to select variables.  You can select multiple variables if you would like to compare historical trends.

If you would like to limit your graph to a particular range of dates, you can also provide a first and last date.

Note:  The Historical Trends task is not included in all student versions of the software.  In some student products the task is accessible only when certain data files are opened.  For information on the tasks available with the full version of the MicroCase Analysis System, contact MicroCase Corporation.

  Click here to see a sample Historical Trends graph


Historical Trends Graph

Once you have chosen your variables, a graph will appear which graphically displays changes in the variables over time.  The x-axis will be the range of years of available data for the selected variables.  In other words, if the selected variables have data available from 1950 to 2000, the x-axis will range from 1950 to 2000.  The y-axis will range from the lowest value on the displayed variables to the highest value on the displayed variables.  For each variable, a shaped marker will be placed at each year for which data is available at its value on the y-axis.  A colored line will then connect the markers, providing a visual display of change in the variable over time.  Each variable will be given a line of a different color and with different year markers.

Below the graph will be a list of important historical events.  When you click on an event, a red line will appear on your trends graph at that year.

The example below shows a historical trends graph for two variables--% URBAN and % NO HS.  Click on the screen shot below for more information.  For example, click on the list of historical events for a description.

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Why Can't I Use Historical Trends with My File?

The Historical Trends task requires that the case name variable in your file be a date variable of the format YYYY.  In other words, the values of this variable must be years—1900, 1970, etc.  When you open a file, Student ExplorIt informs you if the Historical Trends task will be available.


Advanced Statistics

(Help on this topic not available in beta version.)


List of Variables

This is the list of existing variables in the currently opened file.


Search Existing Variables

Variable names and descriptions (but no category labels) are searched for a target phrase.  A list of variables containing the target phrase is then shown.


Full List

This option displays the entire list of variables in the current data file.  Generally, this is used to restore the full list after the search option has been used.


Variable Selection Box

In each task, a box similar to this is provided for each task variable. A variable may be selected in any of several ways: by double clicking on its name in the variable list, by highlighting its name then clicking on the appropriate arrow, by typing its number and pressing enter, or by typing its name (or the first part of its name) and pressing enter. In some tasks, such as correlation, you may select a list of variables.


Subset Option

When subset variables are used, only cases that fall within the requested range on each subset variable are included in the analysis.


Variable Description

As you scroll the variable list, the variable description and the category labels (if any) will appear in this box.


OK Button

When you have finished selecting variables, click on the OK button to continue with your task.


Cancel Button

Click on the Cancel button if you do not wish to continue with the chosen task.


Clear All Button

Click on the Clear All button to remove any currently selected variables (including subset and control variables).


Finding Cases

If you are having trouble finding a case, click on “Find Case.”  A box will then appear with a list of all the cases on your map.

Select the case you want to find by clicking on it.  Click OK and MicroCase will highlight the selected case on your map.  See the screen shot below to learn more about finding cases.  For example, click on the OK button to see what it does.

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  See also


Subset

A subset is a group of cases from your dataset that share a certain characteristic or characteristics.


Control Variable

A control is a variable which is held constant during a statistical analysis.  When a control variable is used, the same type of analysis is conducted for each level of the control variable.  For example, cross-tabulating race and religion while controlling for gender would produce a table between race and religion for each category of gender.


Select Categories for Subset

The categories of the selected variable will appear in this box.  Choose the categories to include or exclude from the analysis.  In the current example only cases who are “FEMALE” will be included in statistical analyses.


Include or Exclude Subset Categories

If you wish to include only the categories you have selected in the statistical analysis, choose “Include Selected Categories.”  If you chose “Exclude  Selected Categories,” MicroCase will remove the categories you have selected from the analysis.  By default, the program will include the categories you select.


Subset Variable Name

The name of the Subset Variable you have chosen will appear here.  In the current example, the user has chosen a variable named “SEX,” which has two categories, “MALE” and “FEMALE.”


OK Button

Click on the OK button to finalize your choice of subset categories.  You will then return to the Variable Selection box, from which you can choose additional subset variables, or continue with the analysis.


Cancel Button

Click on the Cancel button if you decide that you do not want to use the selected variable for a subset.


Search Words and Phrases

Use these boxes to enter different words or phrases you would like to search for in the variable list.  In student versions of MicroCase, you can only enter words into the top box.


Search Options

These options are not available in student versions of MicroCase.  In the full version of MicroCase, you can perform two different types of searches using the options provided.  If you want the program to return only those variables which contains all of the words and phrases you have provided, choose “Select variables which contain ALL of the above words.”  If you are trying to find variables which contain any of the words or phrases you have provided, choose the second option, “Select variables which contain ANY of the above words.”


OK Button

Click on the OK button to continue with your search.  The program will provide a list of all variables which match your search criteria.


Cancel Button

Click on the Cancel button to return to the variable selection box without performing a search.


Univariate Graphs and Statistics

Use the options on the left-hand side of the univariate screen to choose the type of graph you would like to view or to view summary statistics.

Click on the screen shot below to learn more about univariate graphs and statistics.  For example, click on “Pie” to see a description of this function.

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If your variable does not have defined categories, then only summary statistics will be available.

If your variable has defined categories, then click on "Pie" to view a pie graph .  Click on "Bar Freq." to see a regular bar graph or "Bar Cum.%" for a cumulative bar graph.  If you wish to see summary statistics, click on "Summary."

  Learn more about Pie Graphs

  Learn more about frequency Bar Graphs

  Learn more about Cumulative Bar Graphs

  Learn more about univariate summary statistics


Pie Graph

A pie graph displays a frequency distribution as a circle (or pie shape)  with each category shown as a different colored "slice."  The larger the slice the greater the number of cases which fall into that category.


Bar Graph

A bar graph is a diagram of a univariate distribution in which a vertical box represents the frequency of each category.  The height of each box is determined by the relative frequency of the category.


Cumulative Bar Graph

A cumulative bar graph is a diagram of a univariate distribution in which a vertical box represents the cumulative percentage of each category.  The height of each box is determined by the cumulative percentage of the category.


Pie Graph

Click here to view a pie graph.


Bar Graph

Click here to view a frequency bar graph.


Cumulative Bar Graph

Click here to view a cumulative bar graph.


Summary Statistics

Click here to view univariate summary statistics.


Correlation Coefficient

The Pearson correlation coefficient is a measure of association that tells us the degree to which two ratio variables are linearly related.  The square of the correlation coefficient tells the amount of variance in the dependent variable explained by the independent variable.


Regression

A regression equation describes the line (or plane) that best predicts (in the least squares sense) the values of the dependent variable from the values of the independent variable.


Univariate (Frequency) Distribution

A univariate distribution shows the number of cases in each category of a variable.


Mapping Task

If a data file has an attached map, you can view the distribution of a variable by geographical unit.  Each geographical unit will be given a color depending upon its value.  Higher values are given darker colors.


Mean

The mean, or arithmetic average, of a variable is a measure of central tendency of the distribution and is used with ratio (or ordinal variables).


Median

The median, or 50th percentile, of a variable is the value that divides the distribution in half; 50 percent of the sample score above the median and 50 percent score at or below the median.  This is a measure of central tendency which may be used with either ordinal or ratio variables.


Standard Deviation

The standard deviation, or square root of the variance, is a measure of variation of a variable expressed in the same units of measurement as the variable itself.  This should be used only with ratio (and ordinal) variables.


Variance

The variance, a measure of the variation of a variable,  is the average squared deviation scores around the mean.  This should only be used with ratio (or ordinal variables).


N

N is shorthand for the number of cases in an analysis.


Missing Data

Missing data refers to cases which have no data available on the variable(s) of interest.


Confidence Interval

The confidence interval allows you to provide a range for your estimate of a population parameter.  For example, the 95% confidence interval around the mean indicates that you can be 95% sure that the true population mean will fall within this interval.  (Of course, the sample must be randomly selected from the population in order for this estimated range to be valid.)  MicroCase provides both a 95% and 99% confidence interval.


Percentage of Cases

The percentage of cases which fall within each category of the variable.


Cumulative Percentage

The cumulative percentage of cases in a category.  For example, the cumulative percentage for category two of a variable is the percent of the total number of cases which fall into category two and all the categories below it.


Z-Score

A z-score expresses the original value in terms of standard deviations above or below the mean.  For example, a case with a z-score of -1.5 had a value of one-and-a-half standard deviations below the mean.


Category Labels

The categories of your variable will appear here.


Case Name Variable

A case name variable is an alphanumeric variable which contains the name of each case.


Category Label

A category label is the name assigned to each category level of a variable.


Weight Variable

In some studies, certain cases are over- or under-sampled.  In this situation, weights must be applied to the cases during analysis to make the results correct for the population which was sampled.  A weight variable contains the weights that should be applied to the cases.


Auto-Analyzer

Auto-Analyzer is a powerful analysis tool that utilizes artificial intelligence to help you obtain statistics and “factoids” on hundreds of topics.


Historical Trends

The Historical Trends task allows you to view change in a variable over time.


Nominal Variables

A nominal variable is a variable with values that are unordered categories.  In other words, the order of categories for a nominal variable has no inherent meaning.  An example of a nominal variable is gender.


Ordinal Variables

An ordinal variable is a variable with values that can be rank ordered but that are not measured with a fixed unit of measurement.  In other words, with an ordinal variable one can say that a particular value is higher or lower than another but not how much higher or  lower.  For example, a variable with the categories strongly disagree, disagree, neither agree nor disagree, agree, and strongly agree, would be an ordinal variable.


Interval/Ratio Variables

An interval or ratio variable is a variable measured using a standard or fixed unit of measurement.  For example, average annual temperature, measured in degrees, would be an interval/ratio variable.


Partial Gamma

Partial gamma is a measure of association for multivariate tabular analysis of ordinal variables.


Measures of Association

Measures of association are statistics which summarize the strength (and sometimes the direction) of a statistical relationship.


Chi-Square

Chi-square is a probability distribution.  This distribution is used to assess significance of the effect of the independent variable on the dependent variable.


Expected Frequencies

The expected frequency is the number of cases in a cell of a table that would be expected if the two variables were not related to one another.


Row Variable

The row variable is the variable selected for the rows in a cross-tabulation analysis.


Column Variable

The column variable is the variable selected for the columns in a cross-tabulation analysis.


Stacked Bar Graph

A stacked bar graph is a diagram of the cumulative distribution of each category of the row variable across each category of the column variable.


Degrees of Freedom (DF)

The degrees of freedom are the number of values free to vary when computing a statistic.


Probability (P)

The P-value is the probability that the observed value of a statistic is merely the result of random fluctuation of the sample.  P-values of .05 or less are considered statistically significant.


Creating New Files

To create a new MicroCase data file, click on the New button on the File & Data Task Menu, or click on the File menu on the menu bar and then choose "New."

Student MicroCase limits you to 100 cases and 50 variables.  After the file has been created you may create variables and add cases.

When you choose to create a new file, a box will appear in which you need to provide a file name and an optional description.  File names must 8 or fewer characters long and may not contain spaces or any of the following characters: \ / : * ? " < > |.  File descriptions must be 80 or fewer characters.  There are no limitations on the type of characters which may be included in the file description.

Once you have provided a file name and description, click on the OK button to create your new file.  Click on the screen shot below for more information.  For example, click on the Cancel button to see what it does.

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File Name

Enter a file name in this box.  File names must 8 or fewer characters long and may not contain spaces or any of the following characters: \ / : * ? " < > |.


File Description

You may enter an optional file description into this box.  File descriptions must be 80 or fewer characters.  There are no limitations on the type of characters which may be included in the description.


OK Button

Click on the OK button to accept your choice of a file name and description and create your new file.


Cancel Button

Click on the Cancel button to close this box without creating a new file.


Number of Cases and Variables

As this note informs you, files created in Student MicroCase are limited to 100 cases and 50 variables.  In the full version of MicroCase, there is no limit on the number of cases or variables.


Opening Data Files

To open a data file click on the Open File button.  The Open box will then appear on your screen.  Find the file you wish to open, click on it, and then click on the "Open" button.  In student versions of MicroCase, you can only open files from the default directory.  When you open a file in student versions of MicroCase, the program will automatically show you the files in the default directory.

To learn more about the Open box, click on the screen shot below.  For example, click on the box titled “Special Tasks Available” to see a description of special tasks.

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When you click on a file name, the box titled Special Tasks Available will tell you whether any of three special tasks—Auto-Analyzer , historical trends , and/or mapping —are available.  To learn more about these special tasks, choose an item below.

  Introduction to Auto-Analyzer

  Introduction to Historical Trends

  Introduction to Mapping


Using the Toolbar

When you are viewing statistical results or performing a task such as defining a new variable, the MicroCase Toolbar will appear.  Depending on the task you are performing, certain features may or may not be available.  Click on a button below to learn more about it.

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Menu Button

Clicking on the Menu Button at any time will return you to the Task Menu .  For example, click on the Menu Button if you are viewing statistical results and want to return to the Task Menu so that you can perform a different analysis.


Change Variables Button

When you have a statistical result showing on the screen, the Change Variables Button returns you to the variable selection screen for that task.  At this point you can clear previously made variable selections by clicking the Clear All Button or you can modify the variable selections—including controls and subsets.

  See also


Information Button

When you have a statistical result showing on the screen, the Information button provides you with a list of all the variables used in the analysis and their associated descriptions.  Information on any subsets or control variables used will also be listed.

The example below shows the information box for a correlation analysis using four variables, IDEOLOGY, INFORMED?, TV NEWS, and TV PREZ, and a subset variable, EDUCATION.  Click on the screen shot for more information.  For example, click on the Copy to Clipboard Button to see what it does.

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If you are not currently viewing a statistical result, the Information button will show you a list of all the variables in your file.  Click on the screen shot below to learn more about the Variable List box.  For example, click on the box titled “Variable Description” to see what it does.

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Copy to Clipboard

Click on the Copy to Clipboard Button to copy all of the information on the current analysis to the Windows Clipboard.  You can then paste this information into a word processor or other Windows program.


Print Button

Click on the Print Button to print a hard copy of the information on the current analysis.


OK Button

Click on the OK Button to close the information box.


Information on the Current Analysis

Information about the current analysis will be presented here, including the names and descriptions for all included variables, and details on any control variables or subsets used.


Print Button

Click on the Print Button to print a hard copy of the displayed statistical results.


Copy Button

During certain tasks you can click on the Copy Button to copy information to the Windows Clipboard.  For example, during the Data Entry task, you can copy the contents of your data entry grid to the clipboard.  You can then paste this information into another Windows program, such as Microsoft Word.


File Notes Button

Click on the File Notes Button at any time to view the file notes for your data file.  MicroCase data files ship with file notes, which includes the sources of variables, suggested citations, and copyright information.

Click on the screen shot below to learn more about the File Notes box.  For example, click on the “OK” button to see what it does.

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Frequently Asked Questions

If you have a question that is not addressed below or in the Trouble-shooting section, go to MicroCase’s web site at http://www.microcase.com/student/support.html. If the question is not addressed at the web site, send MicroCase a fax (425-641-2539) or e-mail (support@microcase.com) and all relevant questions will be added to the web page.

  How can I insert tables and graphics into a word-processing document?

When the appropriate screen is showing, click on the copy button on the toolbar at the top of the screen.  This will save the graphic or table to the clipboard. Open your word-processing document, position the cursor where you want the graphic or table to appear, and then use the paste command.

If you have pasted a table and the columns are not aligned correctly, you can probably use commands in your word processor to improve the appearance:

1.  In some word processors, you can set a block on the table and then use an option to convert the text to a table.  If you select the “tab” delimiter option, a properly formatted table will appear.

2.  In other word processors,  you can move the cursor above the table and modify the tab settings to improve the column alignment.

  How can I change the student name that appears?

After the software is used (or installed) for the first time, there is no way to change the student name that appears. If you have purchased previously used software, you should be aware that you might encounter other problems in the software.  You should purchase a new copy of the product and reinstall it on your computer.

  How can I delete a variable in a data file I created?

Several student products allow you to create a data file and enter a limited number of variables. If you create a data file and later want to delete a variable you entered, follow these steps: (1) Select the Define & Edit Variables task, (2) use the arrow keys at the top left corner of the screen to scroll to the variable you want to delete, and (3) click the [Delete] button on the left task bar. The variable you selected will be deleted and all variables that follow it will be moved up one number in the variable list. WARNING: a variable that has been deleted no longer exists, so be careful.

  How do I add a recoded variable to the end of a data file when I’ve used up the allotted space?

Several student products allow you to add a limited number of recoded (or collapsed) variables to certain data files provided with the book. Recoded variables are placed at the end of data files and are generally limited to 8 variables. If you have used up each of these allotted spaces, you must replace one of the variables you previously created in order to add another recoded variable. If you used up the 8 spaces reserved for recoded variables, you will be asked to enter the number of the variable you want to replace the next time you try to create a recoded or collapsed variable. Be sure to replace only those variables you do not want to use any more, because once a variable has been replaced it no longer exists. NOTE: You cannot replace one of the original variables provided in a data set--you can only replace those variables you have created yourself.

  How can two different people use their personal versions of the student software on the same computer?

There are two options:

1) Install one copy of the student software to the hard drive, but make sure to select the option to NOT install the data files to the hard drive. Prior to starting Student MicroCase (or Student ExplorIt), the user will need to insert his or her diskette in the floppy drive and then double-click on the shortcut icon to start the program. All changes to data files will be placed on the user’s diskette (that is, changes will not affect other users), and all printouts will show the proper name of the user. We suggest that you use this option when many users have to share the same computer, such as in a lab setting.

2) Install the program and data files in a different directory for each user.  Each person installs a personal copy on the hard drive and also installs all the data files on the hard drive. Each user will be given a different directory and will probably want to create a personal icon on the desktop. We suggest that you use this option when only a few users will be sharing the computer.

  I will be installing a version of Student MicroCase (or Student ExplorIt) from another product published by MicroCase Corporation.  How should I do this?

Just follow the instructions.  The installation process will automatically create a different directory for the second version. At the end of the installation you will want to change the name of the icon so you will be able to distinguish among different products.

  How do I remove the program from my hard drive?

From the start menu on the Windows 95 desktop, select Settings, then select the Control Panel. On the Control Panel, select the Add/Remove Program option. Scroll the list of programs and highlight the program you wish to remove. Then click on the Add/Remove program option. After you have finished, you will have to remove the shortcut icon yourself.

In some cases, you may also need to manually remove data files installed with the program.  If you used the default installation directory when installing the program, any remaining data files will be in a subdirectory of "c:\Program Files\MicroCase\."

  How do I re-install the student software?

The best way to re-install Student MicroCase (or Student ExplorIt) is to first remove the original installation from your hard drive (see the previous section). Then install the program again using the standard installation procedures.

  Should I put my files on the hard drive or use a floppy disk?

Only install the data files on the hard drive if you will always be using the same computer.  If you want to be able to use different computers, perhaps one at school and one at home, you must use the floppy disk.


Troubleshooting

The following section provides answers and suggested solutions to commonly encountered problems and error messages.  If you have a question that is not addressed below or in the Frequently Asked Questions section of Help, go to our web site at http://www.microcase.com/student/support.html. If the question or problem is not addressed on our web site, contact Thomas Learning technical support by calling (800) 423-0563 or sending email to support@kdc.com and we will promptly add all relevant questions to our web page.

Click on a button below for help with a particular type of problem:

  Disk and file problems

  Printing problems

  Working with a network


Disk & File Problems

If you encounter one of the following disk or file-related error messages when running the Windows 95 version of the student software, this is what it means.

  A sharing violation occurred while accessing...

This error message indicates that the data file is already open. Usually this means that another copy of the program is running and the data file is currently open in that program.

  Problem with file name.  Only the following files can be used with ……

A list of files appropriate for use with this product will be given at the end of this message. You will get this message if you have renamed a data file.  In this case, rename the file back to the original name which appears on the list provided with the message.

 [File name] cannot be opened.  It is either a file that did not come with ….. or it has been damaged.

This problem typically occurs if you try to open a data file which was not designed for this product. You may also get this message if you altered the file in the full version of MicroCase. If a data file has been altered or damaged and it is located on a hard drive, you can recopy the original data file from the floppy diskette provided with the book.

  File already exists—must select a different name.

When you are creating a new file, you must select a unique name.

  Cannot find previously created file...

Some student versions of MicroCase allow you to create a data file. If you rename or delete this file using a standard Windows convention (rather than changing the file using MicroCase’s “New File” option), you will encounter the above message. If you renamed the data file, go back and change the name back to the original name you gave it. If you deleted the file, you will need to reinstall a file using the original floppy diskette provided with your book. See “Resetting the New File Option” in the question below.

  New file has already been defined.  Do you want to erase it?

Some student versions of MicroCase allow you to create one data file. Only one data file at a time can be created. To replace a data file you created, you need to use the New File option to rename it. DO NOT use the delete key or the recycling bin (or any other Windows operation) to delete this file. If, however, you deleted this file in Windows 95, there is a way to reset this file so that the New File option works again.

Resetting the New File Option

Follow these instructions if you need to reset your new file option.  First, close the Student MicroCase program. Then use the My Computer feature in Windows 95 to locate the data files (e.g., GSS) for Student MicroCase. If Student MicroCase is accessing your data files from the floppy diskette (such as in a lab setting), then you will find these files on your A or B drive. If you did the standard installation and you installed the file to your hard drive, you will find these files in the C:\Program\Files\MicroCase\CS directory or folder. Once you have found your data files using My Computer, double-click on the application file named RESET. A brief program will run that resets part of Student MicroCase so that you can again create a data file. Answer Y (for Yes) to the prompt warning that a file will be overwritten. You are now returned to the Windows desktop (you may have to click the “x” to first close the DOS box that appears when you run the RESET program). Then restart Student MicroCase.

  Problem reading file from floppy drive.  Check that 3.5 inch diskette is in drive.

This message usually indicates that a required diskette has not been inserted, or has been removed, from the diskette drive.  If you get this message, be sure that your 3.5 diskette is inserted completely into the proper diskette drive.

If your diskette is in the proper drive, this message may indicate a problem with the diskette; i.e. the disk could be unformatted, blank, or write-protected, the disk may have bad sectors, the disk drive may be failing, or the diskette may have a virus.  If you have one of the above problems and need a new diskette, call MicroCase Technical Support at (425) 641-7454.

  Problem reading W95 file from floppy drive.  Check that diskette is in drive.

This message usually indicates that a required diskette has not been inserted, or has been removed, from the diskette drive.  If you get this message, be sure that your 3.5 diskette is inserted completely into the proper diskette drive.

If your diskette is in the proper drive, this message may indicate a problem with the diskette; i.e. the disk could be unformatted, blank, or write-protected, the disk may have bad sectors, the disk drive may be failing, or the diskette may have a virus.  If you have one of the above problems and need a new diskette, call MicroCase Technical Support at (425) 641-7454.

  Problem installing data files.  Check to see if the 3.5 inch diskette is inserted in the floppy drive.

This message usually indicates that a required diskette has not been inserted, or has been removed, from the diskette drive.  If you get this message, be sure that your 3.5 diskette is inserted completely into the proper diskette drive.

If your diskette is in the proper drive, this message may indicate a problem with the diskette; i.e. the disk could be unformatted, blank, or write-protected, the disk may have bad sectors, the disk drive may be failing, or the diskette may have a virus.  If you have one of the above problems and need a new diskette, call MicroCase Technical Support at (425) 641-7454.


Printing Problems

The following sections provide suggested solutions for printer memory problems and problems with color printing.

  Printer memory problems

Some printers may have insufficient memory to print some of the graphics.  For example, the Hewlett-Packard HP4L will not print scatterplots with a large number of cases.  To solve this problem, the amount of memory required by the graphic must be decreased.  From the File pull-down menu at the top of the screen, select the Printer Setup option.  Select the Properties option and select the Graphics option. The available options will differ depending on your printer. Generally at least one of the following will be available:

1.  Change from vector graphics to raster graphics.

2.  Change to a lower level of resolution.  For example, switch from 600 dpi to 300 dpi.

3.  Change the quality of the graphic.  For example, change to coarse or draft quality graphics.

As a last resort, you may capture the entire screen.  With the appropriate screen showing, press the “print screen” button.  This will save the entire screen to the clipboard and you may paste it into your word-processing document.  If you paste it into a paint program, you may edit the image.

  Problems with color printing

If you have a color printer, the graphics will print in color on your printer.  However, if your color printer does not have a color cartridge, you will be asked to insert a color cartridge when you try to print.  You may either replace the cartridge or continue without replacing the cartridge.  If you continue without replacing the cartridge, the resulting image will be somewhat cruder than that obtained on a printer without color capacity.


Working on a Network

Students working with a network version must use the floppy disk that came with the product. (Network administrators are not permitted to install the data files to the network.) Before starting the software, the diskette should be inserted in the A or B drive.

Installation of the network version requires a special license and password. Instructors may get a network license and the installation instructions by contacting MicroCase Corporation.

If the network version is used during exams, the network administrator may remove the Mcnet.hlp file so that the on-line help information will not be available.


Introduction to Student ExplorIt

Student ExplorIt is a modified version of the full MicroCase program and most student materials use this version of the software.  The entire task selection menu for Student ExplorIt fits on one screen.  (Another product, Student MicroCase, allows you to create data files, add new data, and recode existing data and consequently requires two task menu screens.)

Before you can conduct any analysis, you must first open a file—just click on the “Open File” option and select the file you want to use.  After you return to the menu screen, several analysis tasks will now be available—these are indicated by a different color and will highlight when you move the cursor across them.  Different tasks are available with different data files.  Now you simply click on the desired task, select the variables, and examine the results.

If you need additional instructions, consult the “Getting Started” section of your workbook, or locate the appropriate topic using the on-line Help.  If you need help while you are doing an analysis, press F1.  An appropriate help screen will appear.


Introduction to Student MicroCase

Student MicroCase is a modified version of the full MicroCase program.  Student MicroCase allows you to create data files, add new data and recode existing data, as well as analyze existing data.  There are two task selection menus.  The File & Data Menu lists all tasks which allow you to examine and/or modify the data files themselves.  The Statistics Menu lists all the analysis tasks.  The names of these menus are shown at the left of the screen and you move between the two menus by clicking your mouse on the appropriate choice. (Another product, Student ExplorIt, uses only analysis tasks and has only one task menu screen.)

When you start, you will be on the File & Data Menu.  Unless you are creating a new file, you must first open a file—just click on the “Open File” option and select the file you want to use.  After you return to the menu screen, several tasks will now be available—these are indicated by a different color and will highlight when you move the cursor across them.

If you wish to conduct an analysis, you should switch to the Statistics Menu by clicking on this item at the left of the screen.  Now you simply click on the desired task, select the variables, and examine the results.

If you need additional instructions, consult the “Getting Started” section of your workbook, or locate the appropriate topic using the on-line Help.  If you need help while you are doing an analysis, press F1.  An appropriate help screen will appear.


File Settings (ExplorIt)

The File Settings box will automatically appear whenever you open a file.  The File Settings box provides you with information about the open file, including the file description, number of cases, number of variables, the name of the weight variable (if applicable), and the name of the case name variable (if applicable).

The File Settings box also allows you to view a variable list, and/or view the file notes.

Click on the OK button to close the File Settings box.  Click on the screen shot below to learn more about the File Settings box.  For example, click on the File Notes button to see what it does.

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Subset by Range

If you choose an interval-level subset variable, you will be asked to provide a range of variables to use in the subset:

Provide a low value and high value, and the click on OK to continue.

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About Student ExplorIt and Student MicroCase

Click on the Help menu and then “About MicroCase” or “About ExplorIt” to see copyright information and the version number for your copy of Student MicroCase or Student ExplorIt.

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Pairwise or Listwise Deletion

Click here to choose between pairwise or listwise deletion.

In pairwise deletion, a case with missing data is omitted only from the calculations directly involving the variable(s) with missing data; the case is included in calculations in which these variables are not directly involved.

In listwise deletion of missing data, a case containing missing data will be omitted from all calculations.


Significance Test Options

Click here to choose between a one-tailed or two-tailed test of significance.


Finding and Removing Cases in ANOVA and t-Test

The ANOVA and t-Test tasks allow you to find individual cases and, if desired, remove them from the analysis.

To find a case, click on the "Find Case" checkbox.  A list of all of the cases in your data file will then appear:

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Once you click on the OK button, the selected case will be highlighted.  The selected case's values on the variables of interested will also be displayed.

If you would like to remove the selected case, click on the "Remove" button.  MicroCase will then remove the case and re-draw your graph.

  See also


Find Case

Click on the "Case" checkbox to find a case.  A list of the cases in your data file will then appear.

Select a case and click on the OK button.  MicroCase will then highlight the selected case on your graph.


Remove

Click on the Remove button to remove the selected case.  MicroCase will remove the case and redraw your graph.