Advanced Statistics

Catalog description

The advanced class will cover the mathematical basis of concepts from introductory statistics, as well as give students practical experience in hands-on data analysis. The first part of the course will consist of an introduction to random variables and probability distributions, including topics such as conditional probability, moment-generating functions, unbiased estimators, and common discrete and continuous distributions. The second part of the course will introduce hypothesis testing and statistical tests, including topics such as maximum-likelihood estimation, the central limit theorem, t-, z-, and chi-squared tests, and nonparametric methods. The final part of the course will cover ANOVA, and regression models and also introduces topics from Bayesian statistics. Throughout the course, students will perform analyses using the statistical software package R. Prerequisite Course(s): Limited to students in the Chemistry PhD program.