Chi-square test
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A chi-square test is any statistical hypothesis test in which the test statistic has a chi-square distribution when the null hypothesis is true, or any in which the probability distribution of the test statistic (assuming the null hypothesis is true) can be made to approximate a chi-square distribution as closely as desired by making the sample size large enough.
Specifically, a chi-square test for independence evaluates statistically significant differences between proportions for two or more groups in a data set.
- Pearson's chi-square test, also known as the Chi-square goodness-of-fit test
- Yates' chi-square test also known as Yates' correction for continuity
- Mantel-Haenszel chi-square test
- Linear-by-linear association chi-square test
[edit] See also
- General likelihood-ratio tests, which are approximately chi-square tests
- McNemar's test, related to a chi-square test
- The Wald test, which can be evaluated against a chi-square distribution
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