[Home]   PSY 101    [Psychology
                Images]    Research Enterprise in Psychology I: Looking for Laws/Looking for Causes  [OUTLINE]
Last updated: 2/26/2018

Questions from 1st Week of Course (Remember, all of the answers were FALSE)
How would you research any of these questions?

What would you need to do to answer these questions?

A. Looking for Laws: The Scientific Approach to Behavior

Goals of science are

1 Measurement & Description of some phenomenon (good but not yet enough)

2. Understanding & Prediction = Lawfulness

  • Hypotheses
  • Variables

3. Application of Laws & Control (Doing something with the laws)

Theory in science ≠ "theory" in ordinary language

[Theories of Aerodynamics & Germs/Disease]

Steps in a Scientific Investigation

1. Formulate a Testable Hypothesis (that is, some reality we claim is true)

          Question: Are science faculty subconsciously biased against women?
          Hypothesis: Science faculty members ARE subconsciously biased against women.

2. Select the Research Method & Design the Study

  • Experiment? 
  • Case Study? 
  • Naturalistic Observation? 
  • Survey? 
Participants (subjects)

3. Collect the Data

  • Direct Observation
  • Questionnaire (Survey)
  • Interview
  • Psychological Test
  • Physiological Recording
  • Examining Archival Records

4. Analyze the Data & Draw Conclusions

  • Statistics analyze numbers: how much of a difference has to be there for it to be a real difference?
  • Qualitative approaches analyze non-numerical data (e.g., themes, etc.)

5. Report the Findings

  • Scientific journals, for example, in APA Journals
  • Conferences
  • Books, etc. 

 Advantages of a Scientific Approach to Research

B. Looking for Causes: Experimental Research

What is an experiment? A research approach in which the investigator controls the conditions under which research subjects or participants experience variables. In an experiment, the research subjects experience identical (or standard) conditions except for the variable under review.

Hypothesis: Science faculty members ARE subconsciously biased against women

Moss-Racusin et al. (2012)

A. Types of Variables

  • Independent = Controlled by Investigator
  • Dependent = Depends on what happens to the participant
  • Independent => Identical application for a laboratory manager position except for name of applicant which is the independent variable (name = gender)
    • Male name = John vs. Female name = Jennifer
  • Dependent => Participants would read application and then rate the candidate on these dependent variables:
    • Competence: How competent? (on a scale of 1 to 7)
    • Hireability: How likely would you be to hire this applicant? (on a scale of 1 to 7)
    • Mentoring: How willing would you be to mentor this applicant (on a scale of 1 to 5)
    • Salary: What would you suggest be the starting salary (in a range between $15,000 and $50,000)

B. Types of Groups in an Experiment

  • Experimental
  • Control  

In this science faculty member experiment, the control group might actually be considered those who received the male name, i.e., if we are looking if females are treated differently, the male name group would be the standard against which to judge. Thus, the experimental group would be those who got the female name, i.e., we want to see if they will rate the candidate differently than the control group.


[Moss-Racusin results]
  • On each of these dependent variables, there is a significant difference between ratings given male vs. female applicants. Females are always rated below males. The hypothesis is supported.
  • Female & male faculty raters did not differ in their overall pattern of ratings.

C. Problems in an Experiment

  • Extraneous variables
  • Confounding variable
  • Choosing an Experimental Group
    • Need for Random Assignment so that groups are =

D. Types of Design

  • One (1) Independent Variable
  • Two (2) Independent Variables
  • More than 2 independent variables (unusual to have more than 2 IVs)

E. Advantages & Disadvantages of Experiments

  • Advantage: Powerful: Cause & Effect can be isolated
  • Disadvantage: Artificial
  • Disadvantage: Some or even many variables can't be manipulated for practical or ethical reasons


This page originally posted on 1/26/04 and updated on 2/26/2018