We will talk about a very important use of conditional probability in public health and medicine, which is the idea of tools that screen for health outcomes. There are many examples of this, including mammograms for detection of breast cancer, the prostate specific antigen (PSA) for detection of prostate cancer, as well as tests for exposure to infectious diseases, and so forth. We will consider two types of events: i) whether the subject truly has the health condition of interest (let $D$ denote the disease of interest, and $D'$ its complement), and ii) whether a test was positive or not for this outcome (let $+$ denote a positive test and $-$ denote its complement, a negative test). There are several statistics that are used to evaluate the performance of a test, some of which are derivable from each other