STAT 351 introduces distribution-free statistical methods, covering rank tests, permutation methods, and kernel estimation.
Offering recorded · Fall 2026
Historical reviews of Chunming Zhang: Assignments and projects are generally inline with lectures and comprehensive, but students note a lack of practice materials and exams that may not reflect course content.
STAT 371 introduces applied statistical practice for the life sciences using R, covering EDA, inference, ANOVA, and regression.
Offering recorded · Fall 2026
Historical reviews indicate varied workloads. John Davis reported short homework, whereas Cecile Ane assigned a heavy group project and required extra practice. Vivak Patel's course was noted as highly difficult.
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 436 teaches data visualization techniques within data science workflows, covering data preparation, exploratory analysis, and model interpretability.
Offering recorded · Fall 2026
The course uses a flipped format with pre-lecture readings, a large group project, and exams. Some students find it easy to succeed with minimal effort, while others note the material requires deep engagement.
Covers pattern classification, regression, clustering, and dimensionality reduction with a focus on statistical evaluation and Python implementation.
Offering recorded · Fall 2026
Historical reviews of John Gillett, Sebastian Raschka: Workload is generally manageable with recorded lectures, though Gillett's exams can be difficult and require careful review, while one review cites unorganized materials and confusing group policies.
Introduction to deep learning and generative models connecting neural networks to statistical concepts.
Offering recorded · Fall 2026
Historical reviews of Yiqiao Zhong: Reviewers note low overall workload, though exams can be confusing if lecture concepts are not understood. One student found the difficulty manageable with effort, while another cited flexible deadlines and fine tests.
STAT 461 teaches advanced statistical methodologies for modern finance, including discrete and continuous stochastic models.
Offering recorded · Fall 2026
Historical reviews of Yazhen Wang: Reviewers found homeworks difficult and exams tricky, noting that the lack of a textbook and study aids made preparation challenging.
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.
STAT 610 introduces statistical inference, covering distribution theory, limit theorems, parameter estimation, hypothesis testing, Bayesian inference, and nonparametric estimation.
Offering recorded · Fall 2026
Historical reviews of Wei-Yin Loh: Assignments and exams are described as too tricky, with a useless textbook even for open-book exams, potentially causing students to quit before mid-term.
STAT 613 teaches modern statistical methods and data analysis techniques, covering linear regression, diagnostics, prediction, and experimental design.
Turns statistics concepts into practice through data science practicums inspired by realistic projects.
Offering recorded · Fall 2026
Historical reviews of Hyunseung Kang: The class is a lot of work, with grades heavily dependent on randomly assigned group projects and unclear grading criteria.
STAT 703 is a graduate internship course where students apply statistics principles in a professional setting through a full-time practical internship.
STAT 992 is a graduate-level seminar covering special topics in statistics, with subject matter varying by offering.
Offering recorded · Fall 2026
Historical reviews of Joshua Cape: The review does not specify workload or difficulty, only noting the material is delivered in an easy-to-understand way.