Lecture: M,W 2:20-3:35 pm
Office hours: M,W 3:40-4:40 pm

Course Description (from the Duke Statistics graduate course listings)
Probability and Measure. Introduction to probability spaces, the theory of measure and integration, random variables, and limit theorems. Distribution functions, densities, and characteristic functions; convergence of random variables (a.s., L-p, in probability) and of their distributions; uniform integrability and the Lebesgue convergence theorems. Weak and strong laws of large numbers, central limit theorem, conditional probability and expectation and their statistical relevance. Martingales, Sequential Statistical Tests, Brownian Motion.

Grading
The course grade will be based on homework assignments (50%) and two in class exams (25% each).

Exam dates
First exam: Wednesday February 28
Second exam: Wednesday April 18