Introduction to statistics for science and engineering covering descriptive statistics, probability, hypothesis testing, linear regression, and ANOVA using R.
Offering recorded · Fall 2026
Homework is time-consuming, taking five to six hours per set, and exams are challenging with a time crunch. Students must spend significant time understanding homework to prepare for tests that may differ from practice problems.
STAT 424 introduces statistical experimental design, covering randomization, blocking, factorial designs, and response surface methodology with engineering applications.
Offering recorded · Fall 2026
Workload involves writing R code for homework, while exams are often predictable and similar to practice problems, though self-study via the textbook is recommended.
STAT 479 covers special topics in statistics of interest to undergraduate students.
Offering recorded · Fall 2026
Historical reviews of John Gillett, Karl Rohe, Kris Sankaran: Workload varies by instructor; Gillett’s course required independent Linux learning and debugging, while Sankaran’s recent term involved graduate-level assignments. Sankaran’s earlier terms featured spread-out homeworks, and Rohe provided few guidelines.
STAT 601 provides a thorough grounding in modern statistical methods, covering data collection, exploration, probability, and analysis.
Offering recorded · Fall 2026
Historical reviews of Vivak Patel: Reviewers describe a heavy workload with difficult projects and expect students to do significant independent work, noting that graduate-level rigor requires hard work.