ABSTRACT
The t tests and the one-way ANOVA are termed parametric tests in that they depend considerably on population characteristics, or parameters, for their use. Both these tests, for instance, use the sample's mean and standard deviation statistics to estimate the values of the population parameters. Parametric tests also assume that the scores being analyzed come from populations that are normally distributed and have equal variances. The chi-square test is most commonly used in two similar but distinct circumstances: for estimating how closely an observed distribution matches an expected distribution and for estimating whether two random variables are independent. The primary use of the chi-square test is to examine whether two categorical variables are independent or related. A contingency table is a two-way table for examining relationships between categorical variables that have been classified into mutually exclusive categories and where the entries in the cells are frequency counts.
