In this chapter we presented two hypothesis tests that employ the chi-square distribution. In Section 16.1 we discussed a chi-square test of goodness of fit. Here we considered a situation in which we study how count data are distributed among various categories. In particular, we considered a multinomial experiment in which randomly selected items are classified into several groups, and we saw how to perform a goodness of fit test for the multinomial probabilities associated with these groups. We also explained how to perform a goodness of fit test for normality. In Section 16.2 we presented a chi-square test for independence. Here we classify count data on two dimensions, and we summarize the cross-classification in the form of a contingency table. We use the cross-classified data to test whether the two classifications are statistically independent, which is really a way to see whether the classifications are related. We also learned that we can use graphical analysis to investigate the nature of the relationship between the classifications.