Discussion response needed for this post

I have never had the opportunity to use the chi square test in my career, but it seems like a very useful tool when examining relationships between two or more categorical variables. The data being studied is categorical and not continuous, is sampled randomly and is mutually exclusive. According to the lecture this week, the chi square test for independence is the most commonly used. It is used to test that the variables (two or more) of the null hypothesis are independent and not related. I can see this being used to determine the effectiveness of medical treatment. One test group could receive a new drug, the other a placebo and the third a standard treatment. These can then be compared to determine if there is a relationship between the treatment type and the recovery rate. If only one variable is used, the chi square test for goodness of fit is used. The chi square test for goodness of fit tests that the null hypothesis has a good fit with the specified distribution. Finally, the chi square test for homogeneity tests that the null hypothesis has distributions that are the same.