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 if the null hypothesis is true. These include:
- Pearson's chi-square test
- Some likelihood-ratio tests are approximately chi-square tests when the sample-size is large. They are widely used in logistic regression. Other likelihood-ratio tests cannot be regarded as even approximately chi-square tests; e.g., F-tests in the analysis of variance and t-tests are likelihood-ratio tests, but the test statistic does not have a chi-square distribution under the null hypothesis.
- Yates' chi-square test, or Yates' correction for continuity
- Mantel-Haenszel chi-square test
- linear-by-linear association chi-square test
All such tests involve a statistic of the form
- <math>X^2=\sum\frac{(\mathrm{observed}-\mathrm{expected})^2}{\mathrm{expected}},<math>
where the word "expected" often does not denote an expected value, but an observable estimate of an expected value.
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