Hypothesis test

Chi-square Test of Independence

The chi-square test of independence is a nonparametric hypothesis test that examines whether two categorical variables are associated by comparing observed and expected frequencies in a cross-tabulation. It rests on the chi-square criterion introduced by Karl Pearson in 1900.

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Sources

Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175. DOI: 10.1080/14786440009463897 ↗
Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd ed.). Wiley. ISBN: 978-0471226185

Related methods

Cramer's V McNemar's test

Referenced by

A/B Test Bayesian chi-square test Bayesian cross-tabulation analysis Bayesian Fisher's exact test Cochran Q Test Cohen's Kappa Cramer's V Cross-tabulation analysis McNemar's test Power analysis Power Analysis for Proportions Proportion Test Robust chi-square test Robust Fisher's exact test

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