Go to Main Content

.

 

HELP | EXIT

Detailed Course Information

 

Spring 2021
May 09, 2021
Transparent Image
Information Select the desired Level or Schedule Type to find available classes for the course.

MATH 628 - Computational Methods in Statistics
Random variable generation, Monte Carlo methods and numerical integration, Bayesian inference and Markov chain Monte Carlo, Metropolis-Hastings and Gibbs Sampling, basics of numerical optimization such as Newton's method, constrained optimization, Expectation-Maximization algorithms. Prerequisite: MATH 620 or DSCI 602 or permission of the department chairperson.
3.000 Credit hours
3.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture, Online Fixed Times (Synch), Online (Asynchronous), Immersive Learning, Study Abroad, Societal Issue/Global Chal

Mathematical Sciences Department

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

Prerequisites:
Graduate level MATH 620 Minimum Grade of D-

Return to Previous New Search
Transparent Image
Skip to top of page
Release: 8.7.2.4