The underlying principle is that the square of an independent Normal variable has a chi-square distribution with one degree of freedom (df). A second principle is that the sum of k independent chi-squares variables is a chi-squared variable with k df.
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The Chi-squared statistic can be used to test for association.
The Chi-square test is a statistical test that is usually used to test how well a data set fits some hypothesised distribution.
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A F-ratio test compares 2 variances and tell if they are significantly different. A Chi-square test compares count data.
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