Stochastic Processes (MATH-0167)

Spring 2027 · MATH 0167 · Tufts University · 3 credits · Undergraduate

Introduction to discrete-time and continuous-time stochastic processes and their applications. Topics include finite Markov chains (absorbing chains, ergodicity and convergence, reversibility, Monte Carlo methods and mixing times), countable state spaces (Poisson process, birth-and-death chains, branching processes, transience and recurrence), conditional expectation and martingales, optional sampling, and Brownian motion in one and several dimensions. Prerequisites: MATH 70 and either MATH 165 or EE 104. Recommendation: MATH 135 and some prior experience coding in a high-level language such as Python or Matlab.

Course codes: MATH-0167, MATH 0167, MATH0167, MATH-167, MATH 167, MATH167

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