Lecture, three hours. Recommended requisite: course 200B. Recommended preparation: programming skills in R, C/C++, MATLAB. Overview of theory and practice of computer-based methods for statistical inference and uncertainty quantification, including bootstrap, resampling, computer simulation, and Monte Carlo sampling. Coverage of nonparametric and parametric bootstrap, bootstrap inference, permutation test, cross-validation, likelihood approximation, importance sampling, and Markov chain Monte Carlo with brief introduction to Bayesian inference and missing data problems. S/U or letter grading.

Review Summary

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Enrollment Progress

Dec 4, 3 PM PST
LEC 1: 35/35 seats taken (Full)
First passPriority passSecond pass2 days5 days8 days11 days14 days17 days20 days23 days26 days02040

Section List

  • LEC 1

    Open (11 seats)

    MW 2pm-3:15pm

    Physics and Astronomy Building 1749

Course

Previously taught
22W 19W

Previous Grades

A+AA-B+BB-C+CC-D+DD-F0%20%40%60%