Final Exam Time and Place: Tuesday, March 17, 1:00-3:00pm, in Wellman 6.

Material covered on the final: Combinatorial probabilty, (permutations, combinations), consequences of the axioms (inclusion-exclusion), conditional probability, the two Bayes' formulas, independence of events, discrete random variables (expectation, variance, binomial, poisson, geometric), continuous random variables (density, expectation, variance, distribution of a function, uniform, exponential, normal), joint distributions (incl. geometric problems), independence of random variables, central limit theorem (need to know how to use the table for Phi(x), x>0, which will be provided), Poisson approximation, indicator trick. No conditional densities or conditional expectations.

Study tips: Understand all examples we did in the lectures. For exam practice, solve the Practice Final on the Lecture Notes, or the sample final provided here. For additional practice, you can look at problems at the end of each chapter in the Notes, and homework problems. You also need to make sure that you know how to solve problems from the first two midterms.