This week, our class reviewed three types of test statistics (chi-square, lambda, & gamma) that can be utilized to measure association between variables. My biggest takeaway was understanding and being able to simplify each test's utility and what types of variables can be tested with each type of test. Chi-square, for example, can be used to test for variable association or variable significance with nominal variables and Lambda can be used to test for a more accurate measure of association between two nominal variables (and without the use of tables like the chi-square table). Understanding what level of measurement our variables use is important to determine what type of test can be used to test the data