STAT 101 Lecture Notes - Lecture 9: Contingency Table
Document Summary
Stat 101 - introduction to business statistics - lecture 9: bayes theorem. You want to find the probability of cancer given a positive screening test. **** ultimately we wish to find p(c|d). The probability a test comes back negative given no cancer (specificity). The probability a test comes back positive given cancer (sensitivity). The probability of cancer (with no conditioning). (marginal probability) Call c the event that cancer is present. Call cc the event cancer is not present. Call d the event the diagnostic test comes back positive. Call dc the event the diagnostic test comes back negative. **note: the key insight is that these conditional probabilities will allow us to propagate the marginal probabilities back into the cells of the contingency table. Step 1: work out cell counts (assume here that 1000 people have test done) Step 2: fill in the margin based on the prevalence of cancer.
