Courses
Browse our diverse course options.
Master’s Required Coursework
ST 501 — Fundamentals of Statistical Inference I
Description: First of a two-semester sequence in probability and statistics taught at a calculus-based level.
ST 502 — Fundamentals of Statistical Inference II
Description: Second of a two-semester sequence in probability and statistics taught at a calculus-based level.
ST 503 — Fundamentals of Linear Models and Regression
Description: Estimation and testing in full and non-full rank linear models.
ST 517 — Applied Statistical Methods I
Description: Course covers basic methods for summarizing and describing data, accounting for variability in data, and techniques for inference.
ST 518 — Applied Statistical Methods II
Description: Courses cover simple and multiple regression, one- and two-factor ANOVA, blocked and split-plot designs. Data with multiple sources of error such as longitudinal data collected over time and categorical data analysis including regression with binary response will also be covered.
ST 542 — Statistical Practice
Description: This course will provide a discussion-based introduction to statistical practice geared towards students in the final semester of their Master of Statistics degree.
ST 555 — Statistical Programming I
Description: An introduction to programming and data management using SAS, the industry standard for statistical practice.
Ph.D. Required Coursework
ST 701 — Statistical Theory I
Description: Probability tools for statistics.
ST 702 — Statistical Theory II
Description: General framework for statistical inference.
ST 703 — Statistical Methods I
Description: Introduction of statistical methods.
ST 704 — Statistical Methods II
Description: Introduction to additional statistical methods.
ST 705 — Linear Models and Variance Components
Description: Theory of estimation and testing in full and non-full rank linear models.
ST 758 — Computation for Statistical Research
Description: Computational tools for research in statistics, including applications of numerical linear algebra, optimization and random number generation, using the statistical language R.
ST 779 — Advanced Probability for Statistical Inference
Description:Theoretical foundations of probability theory, integration techniques and properties of random variables and their collections.
ST 793 — Advanced Statistical Inference
Description: Statistical inference with emphasis on the use of statistical models, construction and use of likelihoods, general estimating equations, and large sample methods. Includes introduction to Monte Carlo studies, the jackknife, and bootstrap.
ST 810 — Advanced Topics in Statistics: Ethics in Statistics
Description: Initiate conversations about how and why we should conduct ourselves as professional statisticians. Provide practice with oral communication skills and with working in a heterogeneous team environment.
ST 841 — Statistical Consulting
Description: Participation in regularly scheduled supervised statistical consulting sessions with faculty member and client.