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Fall 2026

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9 courses

Historical grades cover up to five years through the selected term. Grade sorting prioritizes courses with at least 100 letter grades.

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

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

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

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.

historical GPA · grades

Spring 2022–Spring 2026

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.

historical GPA · grades

Spring 2022–Spring 2026

STAT 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 2026

STAT 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 2026

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