Monte Carlo Methods
0.5 Credit

Hours per week:
  • Lecture/Discussion: 3
  • Lab: 1.5 (biweekly)

Simulating random numbers from various probability distributions; transformations of uniform variates; sampling from multivariate distributions; simulation of stochastic processes; (quasi-)Monte Carlo methods; variance reduction techniques. Applications may include: numerical integration of multivariate functions in high dimensions; approximation algorithms for solving matrix equations, partial differential equations and integral equations; pricing financial securities; MCMC methods; resampling techniques and other topics of computational statistics.

Additional Course Information
CP104, MA200 or MA201, ST260 or (ST259 and one of ST230, ST231), and a 0.5 MA/ST credit at the 300 level (MA307 is recommended).