Question

In Chi-square goodness of fit and contingency table tests, it is sometimes necessary to reduce the number of classifications used in order to do what? Explain why.

Statistics

Answer 1

In Chi-square goodness of fit and contingency table tests, it is sometimes necessary to reduce the number of classifications used in order to draw valid conclusions from the test.

The Chi-square test is highly sensitive to sample size. When the expected frequency in a cell in the table is small, say less than 5, then if we perform the chi-square test it will lead to erroneous conclusions. Therefore sometimes we reduce the number of classifications and combine groups so as to be able to perform the chi-square test and draw valid conclusions from the same.

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