MATH 682 — Statistical Inference

Conditional probability and Bayes’ Theorem, discrete and continuous univariate and multivariate distributions, conditional distributions, moments, independence of random variables. Modes of convergence, weak law of large numbers, central limit theorem. Point and interval estimation. Likelihood inference. Bayesian estimation and inference. Hypothesis testing.

• Credits: 4
• Faculty: Graduate Studies
• Department: Mathematics and Statistics
• Prerequisite: MATH 141 or equivalent

Sections offered

• Section 001 (Lec), Tue Thu 2:35-3:55 pm · Tue Thu 8:35-9:55 am — 10 seats open