In the last lecture, we covered the basics of hypothesis testing with the HIP mammography study as our example. The study's aim is to determine whether offering mammographies for breast cancer detection reduces the rate of death due to breast cancer. There are 31000 individuals in each of the treatment and control groups; only those in the treatment groups are offered mammographies. We recap the elements of the hypothesis testing framework. In the mammography study, they are: the Parametric Model. We can write indicator variables for whether each patient in the treatment group dies of breast cancer as X1, . ..; X310no - Bernoulli (#), and we can also approximate the total number of deaths as Y = X1 + . . . + X810Do ~ Poisson (X)- The null hypothesis Ho: * = 0.00203 (equivalently > = 63, and the alternative hypothesis HA: *