Tulane University PSYC 3130 Learning Objectives - Chapter 9

These flashcards cover essential terms and definitions related to causation, research designs, correlations, regression analysis, and mediation hypotheses as outlined in the lecture notes.

Criteria for Causation

The necessary conditions required to establish that one variable causes changes in another.

Longitudinal Designs

Research methods that involve repeated observations of the same variables over long periods.

Cross-Sectional Correlations

Correlations measured at a single point in time between different variables.

Autocorrelations

Correlations of a variable with itself across different time points.

Cross-Lag Correlations

Correlations between variables measured at different times, enabling assessment of causation.

Causal Inference

A conclusion about a causal relationship between variables based on evidence from data.

Multiple-Regression Designs

Statistical techniques that predict the value of a dependent variable based on the values of multiple independent variables.

Dependent Variable

The variable that is being measured or predicted in an experiment; the outcome variable.

Independent Variable

The variable that is manipulated or controlled in an experiment to observe its effect on the dependent variable.

Multiple-Regression Table

A statistical table that presents the results of multiple-regression analyses, including coefficients for predictor variables.

Beta Value

A coefficient in a regression model that indicates how much the dependent variable is expected to increase when the independent variable increases by one unit.

Experiments vs. Multiple-Regression Designs

Experiments allow for better control of third variables compared to multiple-regression designs.

Pattern and Parsimony

Concepts in research that emphasize finding simple explanations that account for patterns in data.

Single Studies vs. Parsimonious Patterns

Journalists often report single studies for easier storytelling, despite the complexity that patterns provide.

Mediation Hypothesis

A hypothesis suggesting that a third variable explains the relationship between two other variables.

Testing a Mediation Hypothesis

Steps include establishing that the predictor variable affects the mediator and the mediator affects the outcome variable, along with criteria for significance.

Mediators

Variables that explain the relationship between the independent and dependent variable.

Third Variables

Variables that may influence the relationship between the primary variables of interest.

Moderating Variables

Variables that affect the strength or direction of the relationship between independent and dependent variables.

Bivariate vs. Multivariate Correlations

Bivariate correlations involve two variables, while multivariate correlations involve more than two, allowing for more complex analysis.