ST514 - Statistics For Management and Social Sciences II
- Prerequisites: ST513 or ST511 or ST507
- Term & Frequency: Spring, Summer - Online only
- Student Audience: Graduate students in any field.
- Credit: 3 credits
- Recent Texts: An Introduction to Statistical Methods and Data Analysis, Ott and Longnecker.
- Recent Instructors: Roger Woodard
- Background and Goals: Regression analysis is a flexible statistical problem solving methodology. Students will learn the about regression analysis in depth from topics on basic regression through more advanced techniques. Students will gain considerable experience working with data. Students will use SAS to do most homework assignments.
- Content: Simple linear regression, Regression analysis using linear algebra, multiple linear regression, model building techniques and strategies, variable selection techniques, common pitfalls of regression, residual analysis, logistic regression.
- Alternatives: ST 508, ST 512, ST 516
- Subsequent Courses: None
S1 2017 Sections:
|301||Woodard,Roger||INTERNET|| - ||TBA||14/50 - Open|
|601||Woodard,Roger||Distance Education-I|| - ||TBA||16/50 - Open|