PSY 215: Experimental Psychology - Final Exam Topics

Flashcards for Experimental Psychology Final Exam Review

Confounding Variable

A variable that systematically varies with the independent variable, making it difficult to determine the true effect of the IV on the DV.

Internal Validity Threats

Threats to internal validity include history, maturation, regression toward the mean, and testing effects.

Subject Selection and Attrition Threats

Threats to internal validity related to how participants were selected (subject selection) or if participants dropped out of the study (attrition).

Experimenter Bias

Biases that experimenters can introduce, potentially influencing the outcome of the experiment.

Reasons for Null Results

Possible reasons include weak manipulation, insensitive measures, or insufficient sample size.

Factor

The number of independent variables in a factorial design.

Level

The number of levels for each independent variable.

Between-Subjects Factorial Design

Designs where different participants are assigned to different levels of all IVs.

Within-Subjects Factorial Design

Designs where the same participants participate in all levels of all IVs.

Mixed Factorial Design

Designs that include one or more between-subjects and one or more within-subjects factors.

Main Effect

The effect of one independent variable on the dependent variable, averaging across the levels of the other independent variable(s).

Interaction

Occurs when the effect of one independent variable depends on the level of another independent variable.

Pearson's r Correlation

Indicates the strength and direction of a linear relationship between two variables.

Four Validities of a Pearson's r

Construct, external, statistical, and internal validity.

Three Criteria for Causation

Covariance, temporal precedence, and internal validity.

Causation

Bivariate correlations alone cannot establish causation because they do not satisfy all three criteria for causation.

Slope of Regression Line

Indicates how much the dependent variable is expected to change for every one-unit increase in the independent variable.

Slope

Indicates the strength and direction of the relationship between two variables.

Betas

Shows which variables are the strongest and weakest predictors of Y.

Cross-Lagged Panel Designs

Examines relationships between variables across time to assess temporal precedence.

Partial Correlation and Multiple Regression

Techniques that attempt to control for the influence of a third variable on the relationship between two variables.

Moderating Variable

A variable that affects the direction or strength of the relationship between two other variables.

Mediating Variable

A variable that explains the relationship between two other variables.

Third Variable

A variable that may be the actual cause of the relationship between two other variables.

Quasi-Experimental Design

Lacks random assignment to conditions.

Non-Equivalent Control Group Design

A quasi-experimental design that includes a non-equivalent control group.

Interrupted Time Series Design

A quasi-experimental design where data is collected before, during, and after an intervention.

Field Experiments

Research conducted in a real-world setting.

Internal Validity Threats in Quasi-Experiments

Regression toward the mean, history effects, and subject selection problems.

Small N Studies Data Presentation

Data is typically reported for each individual participant.

Behavior Change Studies/Applied Behavioral Analysis

Studies that assess the impact of an intervention or treatment on behavior.

Stable Baseline

Multiple measurements taken prior to intervention to ensure stability.

Multiple Baseline

Introducing an intervention sequentially across different individuals, behaviors, or settings.

Reversal and Withdrawal Designs

Involves removing the intervention to see if the behavior reverts to baseline levels.

Cause and Effect in Small-N Designs

Assessing the covariation, temporal precedence, and internal validity.