How good is that test?

In Chapter 12 we looked at probabilities of independent events – things that had nothing to do with one another. Here we think about probabilities in situations where we expect to see connections, such as in screening tests for diseases or DNA evidence for guilt in a criminal trial. Goal 13.1. Interpret and buid two way contingency tables. Goal 13.2. Understand how to compute probabilities for dependent events. Table 13.1 summarizes student enrollment at UMass Boston in 2006 by category two ways: graduate/undergraduate and male/female. We can use the data to answer some probability questions about the a random student. • What is the probability that a student chosen at random is an undergraduate? 1 See comment in instructor's manual. 2 This is real data, but not generally interesting. It's here to illustrate some important ideas – we hope to replace it with a better example for that purpose.