Factorial Designs & Analysis (ANOVA)

These flashcards cover key terms and concepts related to Factorial Designs and Analysis of Variance (ANOVA) based on the provided notes.

Factorial Designs

Research designs that allow examination of the effect of two or more factors on a dependent variable.

ANOVA (Analysis of Variance)

A statistical method used to determine if there are significant differences between means of three or more groups.

F value

The ratio of systematic variation to unsystematic variation in ANOVA; large F indicates more systematic variation.

One-way ANOVA

ANOVA with one independent variable (IV) manipulated to examine its effect on a dependent variable (DV).

Two-way ANOVA

ANOVA with two independent variables (IVs) manipulated to examine their individual and interactive effects on a dependent variable (DV).

Main Effect

The direct effect of an independent variable on a dependent variable.

Interaction Effect

How two or more independent variables work together to affect a dependent variable.

Within Subjects Design

An experimental design where the same subjects are used for each condition.

Between Subjects Design

An experimental design where different subjects are assigned to different conditions.

Homogeneity of Variance

An assumption in ANOVA that the variance among the different groups should be approximately equal.

Levene’s Test

A statistical test used to assess the equality of variances for a variable calculated for two or more groups.

Sphericity

An assumption in repeated measures ANOVA that the variances of differences between all combinations of related groups are equal.

Descriptive Statistics

Statistics that summarize or describe the characteristics of a data set.

Bonferroni Correction

A method used to adjust significance levels when multiple comparisons are made to reduce the chance of Type I error.

Main Effects of Exercise and Anti-Depressants

The individual effects of exercise status and anti-depressant dosage on wellbeing scores.

Prediction

A hypothesis regarding how independent variables will influence the dependent variable; often stated before the experiment.

Data Visualization

The graphical representation of information and data, often listed in ANOVA results.