MAT 135B: Stochastic Processes (Spring 2017).
Course materials
All files are in the pdf format, which require the free Adobe Acrobat
reader.
- Lecture
notes (created by Janko Gravner)
- Sample Midterm 1.
- Sample Midterm 2.
- Sample Final.
- Midterm 1 will be on Mon, May 1, 2017, in class. It covers
chapters 9, 10, and 11 of the notes and the first three homework
assignments. Topics: 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). For practice, solve the Practice Midterm 1 (p. 139 in
the Lecture Notes) on your own, then look at the solutions and
solve it again. Then do the same with the Sample Midterm 1
above.
- Midterm 2 will be on Wed., May 31, 2017, in class. It covers
chapters 12, 13, 14, and 15 of the book and homework assignments
4, 5, 6, and 7. Topics: Markov chains, transition matrix, n-step
transition probabilities, classes, recurrence, transience,
aperiodicity, limiting distributions, branching processes. For
practice, solve the Practice Midterm 2 (p. 178 in the Lecture
Notes) on your own, then look at the solutions and solve it
again. Then do the same with the Sample Midterm 2 above.
- Finals
week information.