ST 514
Statistics For Management and Social Sciences II
Section: 651

Course Description

This course provides an in-depth study of building, validating, and predicting using regression models. Topics include multiple linear regression models with both continuous and categorical predictors, model selection techniques, and residual diagnostics. Bayesian regression models are also explored. Categorical data analysis is covered including contingency table analysis and logistic regression models. Students will gain considerable experience working with data. Software is used throughout the course with the expectation of students being able to produce their own analyses.

DE Program

Grad Cert in Applied Statistics and Data Mgmt

SUM1 10W 2020

Instructors

Classes Start:
May 13, 2020
Classes End:
July 24, 2020
Distance Education:
Yes
Class Type:
Lecture
Credits:
3.00
Delivery Method:
Internet
Restrictions:
Prerequisite: ST 513

Tools