Overview
Description
Measure theoretic foundations of probability theory. Random variables and distributions, convergence, laws of large numbers, central limit theorems, random walks, martingales, Brownian motion, special topics.
Requirements
Units
Lecture3
Catalog Details
Offering
Offered: Every Spring
Terms
spring
Attributes
Standard
Learning Outcomes
- understand and apply the fundamental results of measure theory and integration.
- derive and apply convergence theorems in probability and statistics problems.
- apply conditional probability and martingale results to problems in stochastic analysis.