The chi-squared data is often expressed in a cross-tabulation, where each row represents a level or category of one categorical variable, and each column represents a level or category of the other categorical variable.
The value recorded in a cell corresponding to the
Suppose there are r rows, that is, there are r levels of the row variable, and c columns, that is, there are c levels of the column variable.
Since the grand total is a constant, and row total = column total = grand total,
For the cross-tabulation, the total degrees of freedom,
For a chi-squared test, there are two ways to conclude the hypothesis test- using the critical value, and using the p-value.
The critical value for the usual right-tailed test, at level of significance,
The p-value for the usual right-tailed test, for the statistic value,
Note that, the distribution of the chi-squared test statistic under the null hypothesis, which is the chi-squared distribution with
Clearly, the size of the cross-tabulation determines the degrees of freedom of the null chi-squared distribution, which, in turn, is the key point in establishing the rejection rule, and hence, forming the conclusion of the chi-squared test of significance.
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78038 18022 84755 23146 12720 70910 49732 79606
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3) 6 Hours
4) 12.5 Hours
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