 |  Statistics for the Behavioral Sciences, 4/e Michael Thorne,
Mississippi State University -- Mississippi State Martin Giesen,
Mississippi State University -- Mississippi State
Alternatives to t and F
Learning Objectives
After completing this chapter, you should
- be able to compute and use nonparametric alternatives to parametric tests, such as the t test for independent samples (nonparametric alternative––Mann-Whitney U test), the t test for dependent samples (nonparametric alternative––Wilcoxon test) and the one-way ANOVA (nonparametric alternative––Kruskal-Wallis test).
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