Looking for a gentler semester? Start with courses where students have earned higher grades.
Highest historical GPA first. At least 100 letter grades over the five years through the selected term. Grades reflect past outcomes, not workload or a guaranteed result.
Historical grades cover up to five years through the selected term. Only courses with at least 100 letter grades are ranked.
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.
historical GPA · grades
Fall 2022–Spring 2026Turns 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.
historical GPA · grades
Fall 2022–Spring 2026STAT 605 teaches tools for collecting, managing, and analyzing large data sets using Linux, R, and distributed computing.
Offering recorded · Fall 2026
historical GPA · grades
Fall 2022–Spring 2026ECE/MATH/STAT 888 covers advanced topics in the mathematical foundations of data science.
Offering recorded · Fall 2026
historical GPA · grades
Fall 2022–Spring 2026STAT 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.
historical GPA · grades
Spring 2022–Spring 2026STAT 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 2026STAT 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 2026COMPSCI/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 2026Introduction 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 2025STAT 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 2026Introduction 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.
historical GPA · grades
Spring 2023–Spring 2026STAT 998 is a consulting apprenticeship course for graduate or professional students.
Offering recorded · Fall 2026
Historical reviews of Sunduz Keles: Students complete a full consulting process with non-statistical clients, involving training steps and sharing stories with invited data scientists.
historical GPA · grades
Fall 2022–Spring 2026STAT 679 covers special topics in statistics at the master's level, with subject matter varying by offering.
Offering recorded · Fall 2026
historical GPA · grades
Spring 2022–Spring 2026STAT 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.
historical GPA · grades
Fall 2023–Fall 2025Applied 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 2026STAT 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.
historical GPA · grades
Spring 2022–Fall 2025Covers statistical methods for clinical trial design, survival analysis, and sequential monitoring.
Offering recorded · Fall 2026
historical GPA · grades
Fall 2022–Fall 2025Covers 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.
historical GPA · grades
Spring 2022–Spring 2026STATISTICAL 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 2025STAT 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.
historical GPA · grades
Spring 2023–Spring 2026STAT 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.
historical GPA · grades
Spring 2022–Fall 2025STAT 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.
historical GPA · grades
Spring 2022–Spring 2026STAT 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 2026STAT 615 develops mathematical theories and statistical concepts for understanding, predicting from, and criticizing data models.
Offering recorded · Fall 2026
historical GPA · grades
Spring 2022–Spring 2026Theory 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 2025STAT 609 covers mathematical statistics, including probability theory, distribution theory, and limit theorems like the Central Limit Theorem.
Offering recorded · Fall 2026
One reviewer reports that homework and class content differ significantly from the test, requiring preparation for a difficult exam experience.
historical GPA · grades
Fall 2022–Fall 2025Covers 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 2026STAT 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 2025STAT 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 2026STAT 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