### Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

### Prerequisites

*18.440 Probability and Random Variables* or *6.041SC Probabilistic Systems Analysis and Applied Probability*

### Description

This course is an introduction to Markov chains, random walks, martingales, and Galton-Watsom tree. The course requires basic knowledge in probability theory and linear algebra including conditional expectation and matrix.

### Recommended Textbooks

Levin, David Asher, Y. Peres, and Elizabeth L. Wilmer. *Markov Chains and Mixing Times*. American Mathematical Society, 2008. ISBN: 9780821847398. [Preview with Google Books]

Williams, D. *Probability with Martingales*. Cambridge University Press, 1991. ISBN: 9780387985091.

Brémaud, Pierre. *Markov Chains: Gibbs Fields, Monte Carlo Simulation, and Queues*. Springer, 2008. ISBN: 9780387985091. [Preview with Google Books]

### Assignments and Exams

There are 5 homework assignments, 1 midterm exam, and final exam. The midterm and the final exams are closed book, closed notes, and no calculators.

### Grading

ACTIVITIES | PERCENTAGES |
---|---|

Assignments | 50% (10% each) |

Midterm Exam | 15% |

Final Project | 35% |