STSCI 4520

STSCI 4520

Course information provided by the Courses of Study 2018-2019.

This course is designed to provide students with an introduction to statistical computing. The class will cover the basics of programming; numerical methods for optimization and linear algebra and their application to statistical estimation, generating random variables, bootstrap, jackknife and permutation methods, Markov Chain Monte Carlo methods, Bayesian inference and computing with latent variables.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: BTRY 3080 or MATH 4710, enrollment in MATH 2220 and MATH 2240 or equivalents. Previous programming experience is recommended.

Outcomes
  • Students will be able to enter, manipulate and plot data and run basic statistical analyses in R.
  • Students will be able to implement estimators for non-standard statistical problems in R.
  • Students will be able to simulate random variables and random experiments in R.
  • Students will be able to design and implement Monte Carlo methods to evaluate integrals and perform simulations.
  • Students will be able to design and conduct appropriate resampling methods to estimate sampling variance for statistical estimates.

View Enrollment Information

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one laboratory. Combined with: BTRY 4520

  • 4 Credits Stdnt Opt

  • 10240STSCI 4520  LEC 001

  • Prerequisite: BTRY 3080 or Math 4710, enrollment in MATH 2220 and MATH 2240 or equivalents. Previous programming experience is recommended.

  • 10241STSCI 4520  LAB 401

  • 12050STSCI 4520  LAB 402