Listed in: Mathematics and Statistics, as MATH-30
Amy S. Wagaman (Section 01)
This course examines the theory behind common statistical inference procedures including estimation and hypothesis testing. Beginning with exposure to Bayesian inference, the course will cover Maximum Likelihood Estimators, sufficient statistics, sampling distributions, joint distributions, confidence intervals, hypothesis testing and test selection, non-parametric procedures, and linear models. Four class hours per week. Requisite: Probability (Mathematics 14 or 29) or consent of the instructor. Spring semester. Professor Wagaman.