Course description

The second of a two-part sequence on: Probability, random variables, discrete and continuous distributions, order statistics, limit theorems, point and interval estimation, uniformly most powerful tests, likelihood ratio tests, chi-square and F tests, nonparametric tests. PREREQ: MATH 3326 and MATH 3352. Offered Even Years in the Spring Semester.

Planned topics (Spring 2026)

  • Parameter Estimation Basics
  • Parameter Uncertainty (confidence intervals / regions)
  • Hypothesis testing
  • Bootstrap

Optional topics

  • Survey Sampling (Chapter~7)
  • Empirical Bayes
  • Introduction to Monte Carlo
  • EM Algorithm / Gaussian Mixture Models
  • Topics in Bayesian statistics (Metropolis-Hastings, Gibbs samplers, MCMC, etc.)
  • Nonlinear regression
  • Introduction to Time Series

Additional Course Information:

Class notes

Current Course Notes

Homework and participation assignments

Please read the grading rubric before submitting homework.

Midterm

Final Exam

TODO: Update.

The final exam will be help in our regular classroom on Dec 18, 10:00 a.m. – 12:00 p.m. The final exam will be comprehensive, closed book.

Acknowledgements and License

This course and the code involved are made available with an MIT license. Some components follow a Creative Commons Attribution non-commercial license. A longer list of acknowledgments is available.