Statistical Computing (344-0-20)

Instructors

Jiping Wang
847.467.6896
Department of Statistics, Room 101B, 2006 Sheridan Road, Evanston
Office Hours: TBA or contact instructor

Meeting Info

Kresge Centennial Hall 2-415: Tues, Thurs 12:30PM - 1:50PM

Overview of class

This course is intended to teach students to use R programming to realize various computing-based statistical analyses. Students will learn the theory and methods related to computational statistics for simulations and statistical inference. Topics include Monte Carlo simulation, Markov Chain and Monte Carlo, Bootstrap, Jackknife, and Gibbs sampling etc.

Registration Requirements

Prerequisite: Stat 320-2, some R programming experience is desired

Learning Objectives

Using R programming to realize various computational statistics methods for simulations and statistical inference.

Evaluation Method

Weekly homework and midterm and final exams

Class Materials (Required)

Computational Statistics by Geof H. Givens and Jennifer A. Hoeting, 2012 Edition.

Class Attributes

Formal Studies Distro Area