MAT 135B: Stochastic Processes (Spring 2017)

     Finals week information:

Final Exam Time and Place: Tuesday June 13, 8am-10am, Roessler 55.

Material covered on the final: Topics covered by Midterm 1 (indicator trick, variance-covariance formula, convergence in probability, moment generating functions (incl. large deviation bounds but no central limit theorem), conditional distributions, expectations, computing probabilities and expectations by conditioning (incl. sums with random number of terms)) and Midterm 2 (Markov chains, transition matrix, n-step transition probabilities, classes, recurrence, transience, aperiodicity, limiting distributions, branching processes), plus reversible chains, renewal theorem, Poisson process.

Study tips: Understand all examples we did in the lectures. You also need to make sure that you know how to solve problems from the first two midterms. Make sure to review homework problems. For practice, solve the Practice Final (p. 210 in the Lecture Notes) on your own, then look at the solutions and solve it again. Then do the same with the Sample Final.