- F-Test/Analysis of Variance — One Way, Equal or Unequal Sample Size
- F-Test/Analysis of Variance — Two Way, Equal Sample Size
- F-Test/Analysis of Variance — Three Way, Equal Sample Size
- Tukey’s Method — tests all possible pairwise differences of means
- Scheffe’s Method — tests all possible contrasts at the same time
- Bonferroni’s Method — tests, or puts simultaneous confidence intervals around a pre-selected group of contrasts
The N-way F-Test is designed to execute within groups defined by the distinct values of the group-by variables (GBVs), the same as most of the other nonparametric tests. Two or more treatments must exist in the data within the groups defined by the distinct GBV values.
Given a column of interest (dependent variable), one or more input columns (independent variables) and optionally one or more group-by columns (all from the same input table), an F-Test is produced. The N-Way ANOVA tests whether a set of sample means are all equal (the null hypothesis). Output is a p-value which when compared to the user’s threshold, determines whether the null hypothesis should be rejected.