Analysis of Variance (ANOVA)

Flashcards covering key vocabulary and concepts related to Analysis of Variance (ANOVA), including types of ANOVA, variance, hypotheses, p-value, degrees of freedom, and related terms.

Analysis of Variance (ANOVA)

Tests if there is a difference between > 2 groups/conditions

One-way ANOVA

One IV with > 2 levels

Within-participant ANOVA

Use within-participant ANOVA for designs where the IV is manipulated within participants.

Between-participants ANOVA

Use between-participants ANOVA for designs where the IV is manipulated between participants.

Variance

Difference between scores

How ANOVA Works

Compares the variance between groups/conditions with the variance within groups/conditions

F ratio

between variance/within variance

Normality

Data is distributed normally within each group/condition

Sample independence

Each sample has been drawn independently of the other samples

Variance equality (homogeneity of variance)

The variance of data in the different groups/conditions should be the same

H0 (Null Hypothesis)

The means of all groups/conditions are equal

H1 (Alternative Hypothesis)

The mean of at least one group/condition is different

P-value

The probability of obtaining results at least as extreme as the observed data, assuming that the null hypothesis (H₀) is true.

Within Factors

IV is manipulated within participants; each participant provides data for all conditions; also called repeated measures

Between Factors

IV is manipulated between participants; each participant provides data for just one condition; also called independent measures

Synaptic pruning

The developmental process where the brain eliminates synapses

Degrees of Freedom (df)

Represents the number of independent values available for estimation after accounting for constraints.

Between-group df

k−1 (where k is the number of groups)

Within-group df

N−k (where N is the total number of observations)

Total df

N−1 (where N is the total number of observations)

Degrees of freedom for conditions (treatment effect)

k−1 (k is the number of levels of the IV)

Degrees of freedom for subjects (individual differences)

n−1 (n is the number of participants)

Degrees of freedom for error (residual variance)

(k−1) × (n−1)