Chapter Summary

Chi-squared tests compare observed counts in a contingency table or discrete distribution to expected counts produced by a null hypothesis. The null hypothesis in the chi-squared test of independence specifies that two categorical variables are independent. Independence of the variables means that the column percentages in a contingency table ought to be similar in the several columns (or equivalently that the row percentages ought to be similar in the rows). The null hypothesis in a chi-squared test of goodness of fit specifies that the distribution of a categorical variable match prespecified percentages. The chi-squared distribution with the appropriate number of degrees of freedom determines the p-value of these tests. The ...

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