Statistical Sciences 2035 Study Guide - Quiz Guide: Null Hypothesis, Chi-Squared Test, Chi-Squared Distribution
7 Oct 2018
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Chi square is the most common and simple non-parametric test of significance suitable for nominal data where observations can be classified into discrete categories and treated as frequencies. After surveying the required data, cross- tabulation tables will be created which state the different categories and the types as well as numbers of individuals. For example, the association between preferences for toothpaste and respondent gender: Chi square tests hypotheses about the independence (or alternatively the association) of frequency counts in various categories. The hypotheses for the chi square test are: H0: the variables are statistically independent or no statistical association, and. H1: the variables are statistically dependent or associated. The formula for chi square is the summation for each cell of: O = observed frequency (value of one cell); e = expected frequency (average of category sum) This kind of test includes any tests that measure how closely observed sample data fit a particular hypothesized distribution.
