Autumn 2022 STAT 24410

Course: STAT 24410=30030

Title: Statistical Theory and Methods Ia

Instructor(s): Daniel Sanz-Alonso

Teaching Assistant(s): Hai Tran Bach and Yi Wang

Class Schedule: Sec 1: TR 11:00 AM-12:20 PM in Stuart 105

Description: This course is the first quarter of a two-quarter sequence providing a principled development of statistical methods, including practical considerations in applying these methods to the analysis of data. The course begins with a brief review of probability and some elementary stochastic processes, such as Poisson processes, that are relevant to statistical applications. The bulk of the quarter covers principles of statistical inference from both frequentist and Bayesian points of view. Specific topics include maximum likelihood estimation, posterior distributions, confidence and credible intervals, principles of hypothesis testing, likelihood ratio tests, multinomial distributions, and chi-square tests. Additional topics may include diagnostic plots, bootstrapping, a critical comparison of Bayesian and frequentist inference, and the role of conditioning in statistical inference. Examples are drawn from the social, physical, and biological sciences. The statistical software package R will be used to analyze datasets from these fields and instruction in the use of R is part of the course.