Applied Regression Analysis
Durham
Engineering&Physical Sciences :: Mathematics&Statistics
Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:
15
CRN: 15225
CRN: 15225
Statistical methods for the analysis of relationships between response and input variables: simple linear regression, multiple regression analysis, residual analysis and model selection, multi-collinearity, nonlinear curve fitting, categorical predictors, analysis of variance, analysis of covariance, examination of validity of underlying assumptions, logistic regression analysis. Emphasizes real applications with use of statistical software. Prereq: MATH 539 (or 644). Writing intensive.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Only listed campus in section: Durham, Manchester
Attributes: Writing Intensive Course
Instructors: Michelle Capozzoli
Times & Locations
| Start Date | End Date | Days | Time | Location |
|---|---|---|---|---|
| 8/30/2021 | 12/13/2021 | MWF | 8:10am - 9:30am | ONLINE |
Booklist
Recommended Text:
Montgomery, D. et al, (2012). Introduction to Linear Regression Analysis, 5th Edition. Wiley ISBN: 978-0-470-54281-1
Weisberg, S. (2014). Applied Linear Regression, fourth edition, Hoboken NJ: John Wiley. ISBN 978-1-118-38608-8