Matt Hester
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Course Library

Every public course-material site I maintain, together with the graduate courses whose materials are still being built. Undergraduate and graduate records sit in one catalog rather than in separate destinations, ordered by curriculum rather than alphabetically.

Records that link out have a public course site. A course whose materials are in development, and a planning-stage curriculum direction, are shown as plain text with nothing to click.

Browse: All · Undergraduate · Graduate · Current

More ways to filter

Material status: Maintained reference · In development · No public materials · Curriculum direction

Curriculum grouping: Introductory statistics · Probability and inference · Modeling and regression · Design and causal evidence · Bayesian methods · Resampling and robust methods · Computing and workflow · Mathematical statistics

Undergraduate course sites

Public course-material sites, each a self-contained collection of notes, labs, and references.

Intro to Statistics

UndergraduateIntroductory statisticsCourse status: Current offering

Data, evidence, models, uncertainty, and simulation.

Open the course site

Intro to Mathematical Software

UndergraduateComputing and workflowCourse status: Current offering

LaTeX, R, Quarto, reproducible workflow, and careful AI-assisted work.

Open the course site

Introduction to Probability

UndergraduateProbability and inferenceCourse status: Maintained public reference

Sample spaces, conditioning and Bayes' rule, random variables, the standard distributions, and simulation.

Open the course site

Statistical Inference

UndergraduateProbability and inferenceCourse status: Maintained public reference

Sampling distributions, likelihood, confidence intervals, hypothesis tests, the bootstrap, and Bayesian inference.

Open the course site

Statistical Modeling

UndergraduateModeling and regressionCourse status: Maintained public reference

Regression, diagnostics, adjustment and interactions, prediction and validation, and logistic regression.

Open the course site

Applied Statistical Methods

UndergraduateModeling and regressionCourse status: Maintained public reference

Group comparisons and ANOVA, regression and ANCOVA, contingency tables, and logistic regression.

Open the course site

Design, Experiments & Causal Evidence

UndergraduateDesign and causal evidenceCourse status: Maintained public reference

Sampling versus assignment, bias and confounding, blocked and factorial experiments, causal diagrams, and study critique.

Open the course site

Bayesian Statistics

UndergraduateBayesian methodsCourse status: Maintained public reference

Priors, likelihoods, and posteriors; Bayesian regression, model checking, and hierarchical models.

Open the course site

Resampling, Nonparametric & Robust Methods

UndergraduateResampling and robust methodsCourse status: Maintained public reference

Permutation and randomization tests, the bootstrap, rank-based methods, and robust estimation.

Open the course site

Modern SAS for Statistical Analytics

UndergraduateComputing and workflowCourse status: Maintained public reference

DATA steps, PROC SQL, cleaning and validation, the core procedures, ODS output, and reproducible reporting.

Open the course site

Graduate statistics curriculum

The mathematical-statistics sequence. These are established catalog courses; what is still being assembled is their public material.

Mathematical Statistics I

GraduateMATH 75063Mathematical statisticsCourse status: In development

Probability, likelihood, and estimation: sampling distributions, convergence, sufficiency, and information. Public materials are still being assembled, so dates, policies, and assessments remain provisional.

No public course site yet

Mathematical Statistics II

GraduateMathematical statisticsCourse status: No public materials yet

The established second course in the sequence: hypothesis testing, interval procedures, decision theory, asymptotics, and resampling.

No public course site yet

Graduate curriculum directions

Planning-stage areas of the curriculum. Not scheduled courses, not adopted requirements, and not in-development course sites.

Regression and Generalized Linear Models

GraduateModeling and regressionCourse status: Curriculum direction

Graduate regression resting on the estimation and likelihood theory of the mathematical-statistics sequence. A planning-stage direction, not a scheduled course.

Not a scheduled course

Computational Statistics

GraduateComputing and workflowCourse status: Curriculum direction

Computation as a tool for statistical reasoning, with reproducible analysis as the working standard. A planning-stage direction, not a scheduled course.

Not a scheduled course

Bayesian Modeling

GraduateBayesian methodsCourse status: Curriculum direction

Graduate Bayesian modeling and workflow, following the conditional-probability and likelihood foundations of the mathematical-statistics sequence. A planning-stage direction, not a scheduled course.

Not a scheduled course

Causal Inference

GraduateDesign and causal evidenceCourse status: Curriculum direction

Estimands, identification, and causal reasoning at the graduate level. A planning-stage direction, not a scheduled course.

Not a scheduled course

No matching items
About course statuses

Status describes the public materials, not whether a course exists.

  • Current offering — tied to a presently scheduled section.
  • Maintained public reference — a durable, public resource collection that is not currently representing a scheduled section. Dates, weights, and final policies are not set here.
  • In development — materials are still being assembled, so dates, policies, assessments, and readings remain provisional.
  • No public materials yet — the course is real and established, but nothing public exists for it.
  • Curriculum direction — a planning-stage area of the curriculum. Not a scheduled course, not an adopted requirement, and not an in-development course site.

Anything operational for a live section — meetings, dates, assessments, grades, and announcements — belongs in the LMS, not here.

See the Teaching overview for current courses, the teaching approach, the Course Builder harness, and the Math Assistance Center.

© 2026 Matt Hester

 

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