ABSTRACT
This chapter discusses different statistics for comparing groups. It uses a one-sample t test to compare one group or sample to a hypothesized population mean. The chapter examines two parametric and two nonparametric/ordinal statistics that compare two groups of participants. It shows how to use the nonparametric Wilcoxon test for a within-subjects design. The One-Sample Statistics table provides basic descriptive statistics for the variable under consideration. When investigating the difference between two unrelated or independent groups (in this case fast track and regular track students) on an approximately normal dependent variable, it is appropriate to choose independent samples t test if the following assumptions are not markedly violated. A Kruskal–Wallis nonparametric test was conducted to test for statistically significant differences between father’s education groups in math achievement because there were unequal variances and ns across groups. The general linear model Univariate program allows you to print the means for each subgroup (cell) representing the interaction between the two independent variables.
