GPA and percentages are weighted by recorded letter grades. UW
comparisons use the same terms. Cross-listed courses count once within
this department and once across UW; department totals should not be
added together. Grade counts are not unique students. Offering counts
reflect captured records, not a complete historical schedule.
Fall 2026
Recorded this term
5757courses with offerings
138138instructors recorded
Grades have not been recorded for this term. Historical results remain
in the overview above.
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57 courses
Historical grades cover up to five years through the selected term. Grade sorting prioritizes courses with at least 100 letter grades.
Introduction to biostatistics for biomedical researchers, covering descriptive statistics, hypothesis testing, regression, and survival analysis with biomedical applications.
Offering recorded · Fall 2026
Historical reviews of Ismor Fischer, Mary Lindstrom: Reviewers describe the course as easy, with take-home or open-note exams. Prior intro stats knowledge makes the material manageable.
Introduces linear optimization problems, emphasizing formal proofs, the simplex method, duality theory, and theorems of the alternatives.
Offering recorded · Fall 2026
The course is considered very difficult, with hard assignments that require significant study time, though group work is permitted. Exams are reported as easier than homework, although one student found the final exam unexpectedly difficult despite its stated format.
Undergraduate Cooperative Education providing full-time work experience that combines classroom theory with practical knowledge in Computer Sciences, Data Science, Statistics, or Information Science.
Introduction to combinatorics covering enumeration, generating functions, graph theory, and matching problems.
Offering recorded · Fall 2026
The course is dense and challenging. Homework is feasible but requires reading the textbook, as lectures may not fully explain concepts. Exams often draw directly from the book and previous tests.
STATISTICAL METHODS FOR BIOSCIENCE I covers statistical inference, ANOVA, regression, and diagnostics for bioscience applications.
Offering recorded · Fall 2026
Historical reviews of Bret Larget, Debraj Das: Exams can be difficult and heavily weighted, with one reviewer noting they covered unseen material, while another found them fair and focused on required knowledge.
Introduction to stochastic processes covering Markov chains, point processes, and renewal theory with applications to queueing and branching models.
Offering recorded · Fall 2026
Seppalainen assigns challenging homework that is harder than exams, while Valko uses a grading scheme based on multiple weighted components rather than heavy testing.
Introduction to mathematical statistical inference, focusing on likelihood, estimation, and hypothesis testing.
Offering recorded · Fall 2026
The course is described as difficult and intense, with long homeworks, high-stakes exams, and a significant gap between lecture content and test material.
Introduction to the theory of probability covering axioms, distributions, and limit theorems
Offering recorded · Fall 2026
Historical reviews of Benedek Valko, Erik Bates: Workload varies by instructor; one review cites an extremely challenging final, while another notes fair homework and adjusted exam weights to reward improvement.
Theory of Probability I introduces measure theoretic probability and stochastic processes.
Offering recorded · Fall 2026
Historical reviews of Hao Shen, Jun Yin: Jun Yin's materials were hard with a weird curve, while Hao Shen was very test-heavy and did not provide proper preparation for exams.
STAT 240 introduces reproducible data science modeling and statistical inference using R and R Markdown.
Offering recorded · Fall 2026
Students report that exams are significantly harder than lectures and homework, with unclear instructions and arbitrary difficulty. Self-study is often necessary due to the disconnect between taught material and assessments.
STAT 303 teaches using the R language to manipulate data and perform exploratory data analysis.
Offering recorded · Fall 2026
The course involves multiple quizzes, homework assignments, and an exam, with reviewers noting the workload is substantial despite the straightforward nature of the tasks.
Introduction to mathematical statistics covering probability, distributions, the central limit theorem, and estimation.
Offering recorded · Fall 2026
Historical reviews of Amy Beyler, Derek Bean, Yaoguo Xie: Workload and difficulty vary significantly by instructor. Some report high-quality materials and fair tests, while others describe difficult exams and a need for extensive self-study to gain solid knowledge.
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.
Applied Regression Analysis covers linear regression for prediction and interpretation, including feature selection, assumption checking, and extensions like mixed and generalized linear models using R.
Offering recorded · Fall 2026
Weekly homework is described as long and unrelated to lectures, while the final project is considered very important and strictly graded. Students report dealing with shifting deadlines and vague test questions that rely on the professor's interpretation.
STAT 340 teaches data exploration, modeling, and analysis using R, covering probability, simulation, hypothesis testing, Bayesian inference, regression, and machine learning techniques.
Offering recorded · Fall 2026
Reviewers consistently report that exams are extremely difficult, often unrelated to lectures or homework, with low averages and insufficient time for paper-based tests.
Introduction to time series analysis covering stationarity, AR/MA models, and forecasting applications.
Offering recorded · Fall 2026
Historical reviews of Panduan An: Reviewers describe the course as difficult, with homework questions being very hard and a high drop rate before the midterm. The lecture pace is often too fast to take notes, and prereqs do not adequately prepare students for the workload.
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.