Master this deck with 23 terms through effective study methods.
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Used to compare means across three or more groups.
When comparing more than two groups or conditions.
T-tests compare only two groups, while ANOVA handles three or more.
Summarize known data from a sample.
To make predictions or test hypotheses about a population.
The outcome measured in an experiment.
The factor manipulated to observe its effect.
Increased risk of Type I error due to multiple comparisons.
Comparing memory performance across different age groups.
Within-participants and between-participants designs.
Participants experience all levels of the independent variable.
Each participant is assigned to only one level of the independent variable.
It compares variance between groups to variance within groups.
A larger difference between group variance compared to within-group variance.
The means of all groups are equal.
Strong evidence against the null hypothesis.
Insufficient evidence to reject the null hypothesis.
Larger samples can yield small p-values even for trivial effects.
Within factors involve repeated measures; between factors involve independent measures.
k - 1, where k is the number of groups.
N - k, where N is the total number of observations.
There is a difference between the conditions tested.
To identify where the differences between groups lie.