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STAT

Statistics

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The department at a glance

All recorded grades
average GPA
A / AB grades
letter grades

How grades break down

Grades over time

Red: department · Gray: UW–Madison

About these statistics

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
courses with offerings
instructors 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.

historical GPA · grades

Fall 2022–Fall 2025

Covers statistical methods for clinical trial design, survival analysis, and sequential monitoring.

Offering recorded · Fall 2026

historical GPA · grades

Fall 2022–Fall 2025

STATISTICAL METHODS FOR MEDICAL IMAGE ANALYSIS introduces statistical methods for analyzing medical images and imaging data.

Offering recorded · Fall 2026

historical GPA · grades

Spring 2022–Spring 2025 · limited sample

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.

historical GPA · grades

Spring 2022–Spring 2026

Covers theory and algorithms for nonlinear optimization, focusing on unconstrained methods like quasi-Newton and trust-region techniques.

Offering recorded · Fall 2026

Assignments are graded harshly, and the course is notoriously difficult, requiring significant preparation to keep up with the rigorous material.

historical GPA · grades

Spring 2022–Spring 2026

Undergraduate Cooperative Education providing full-time work experience that combines classroom theory with practical knowledge in Computer Sciences, Data Science, Statistics, or Information Science.

Offering recorded · Fall 2026

historical GPA · grades

Fall 2025–Fall 2025 · limited sample

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.

historical GPA · grades

Spring 2022–Spring 2026

COMPSCI/STAT 403 allows students to earn academic credit for outside internships related to Computer Sciences or Data Science programs.

Offering recorded · Fall 2026

historical GPA · grades

Spring 2022–Spring 2026

ECE/MATH/STAT 888 covers advanced topics in the mathematical foundations of data science.

Offering recorded · Fall 2026

historical GPA · grades

Fall 2022–Spring 2026

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.

historical GPA · grades

Fall 2022–Fall 2025

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.

historical GPA · grades

Spring 2022–Spring 2026

Introduction to probability and mathematical statistics covering distributions, moments, and estimation.

Offering recorded · Fall 2026

The workload includes ten homeworks, one midterm, and one final, with exams described as easy if students engage with the provided materials.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

Mathematical Statistics I introduces measure theoretic probability, high-dimensional statistics, and large sample theory methods.

Offering recorded · Fall 2026

Historical reviews of Yazhen Wang: Reviewers characterize the class as very hard, with a difficulty rating of 4.

historical GPA · grades

Fall 2022–Fall 2025 · limited sample

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.

historical GPA · grades

Fall 2022–Fall 2025

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.

historical GPA · grades

Spring 2022–Spring 2026

Introduction to statistical methods covering distributions, inference, regression, and experimental design.

Offering recorded · Fall 2026

Workload is described as manageable with straightforward exams, though success requires consistent effort and engagement with the material.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

STAT 304 teaches advanced R programming skills for statistics, including data manipulation, text extraction, and visualization.

Offering recorded · Fall 2026

One reviewer notes the course content was manageable due to prior job experience, though they earned an A.

historical GPA · grades

Spring 2022–Spring 2026

STAT 305 teaches students to use the R statistical language and integrate it with high performance computing tools for scientific computing.

Offering recorded · Fall 2026

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Fall 2022–Fall 2025

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.

historical GPA · grades

Spring 2022–Spring 2025

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.

historical GPA · grades

Spring 2022–Spring 2026

STAT 405 teaches tools for collecting, managing, and analyzing large data sets using Linux, R, and distributed computing.

Offering recorded · Fall 2026

The course involves heavy and hard homework assignments with tight and strict deadlines, even for students with flexible accommodation needs.

historical GPA · grades

Spring 2023–Spring 2026

STAT 421 teaches techniques for analyzing categorical response data, including contingency tables and regression modeling, using R.

Offering recorded · Fall 2026

The workload is relentless, consisting of approximately 66% homework with four to six hours of work per week across multiple large assignments.

historical GPA · grades

Fall 2022–Fall 2025

Across course levels

Recorded this term

No released grades for this term.

Recorded offerings over time

Offering snapshots currently cover Fall 2026. Earlier grade records do not provide a complete offering history.