Manipulation and Control of Variables (College Board AP® Psychology): Revision Note

Independent & dependent variables

• A variable is any factor that can change or vary

  • In psychological research, variables allow researchers to examine:

    • cause-and-effect relationships in experiments

    • associations between factors in correlational studies

• Key variables in experimental research include:

  • the independent variable

  • the dependent variable

  • confounding variables

Independent variable

• The independent variable is the factor that is deliberately manipulated by the researcher in an experiment

  • It is the variable that is changed to determine whether it causes an effect on another variable

• Examples of independent variables:

  • Participants study a word list in silence or with loud music

    • The IV = study condition (silence vs. loud music)

  • Participants complete a task after 30 minutes of exercise or no exercise

    • The IV = exercise condition (exercise vs. no exercise)

  • Children observe an aggressive model or a non-aggressive model

    • The IV = type of model observed

• In a true experiment:

  • The IV is deliberately manipulated

  • Participants are typically randomly assigned to conditions

  • The DV is measured

• When confounding variables are controlled, manipulating the IV allows researchers to determine whether changes in the DV were caused by the IV

  • This strengthens internal validity

• If the “IV” is naturally occurring (e.g., age, gender, ethnicity), the researcher did not manipulate it

  • In this case, the study is not a true experiment but rather a quasi-experiment

    • Because there is no random assignment, cause-and-effect conclusions are weaker.

Dependent variable

• The dependent variable is the outcome that is measured

  • It represents the effect of the independent variable

• Examples of dependent variables:

  • The number of items correctly recalled

  • The time (in seconds) to complete a puzzle

  • The number of aggressive acts performed

• The DV must be measurable so that results can be analyzed and compared across conditions

Confounding variables

• A confounding variable is a factor other than the IV that differs between groups and influences the DV

  • A confound creates an alternative explanation for the results

• If a variable systematically varies with the IV and affects the DV, it threatens the study’s internal validity

• Examples of confounding variables:

  • Time of day (participants may perform better in the morning)

  • Room temperature

  • Participant personality

  • Prior experience with the task

• If one group is tested in the morning and the other in the afternoon, time of day becomes a confounding variable because it differs between groups and may influence performance

Extraneous vs. confounding variables

• An extraneous variable is any variable other than the IV that could affect the DV

• A confounding variable is an extraneous variable that actually differs between groups and influences results

• It is impossible to eliminate all extraneous variables, but researchers attempt to prevent them from becoming confounds

Controlling confounding variables

• Researchers attempt to control confounds to ensure that changes in the DV are caused by the IV

• Common control methods include:

  • Random assignment

    • Distributes participant differences evenly across conditions

  • Standardized procedures

    • Keeping instructions, environment, and timing consistent

  • Controlling the environment

    • Same room, same temperature, same time limit

  • Counterbalancing (in repeated measures design)

    • Controls order effects by varying the order of conditions

• Strong experimental control increases internal validity and strengthens causal conclusions