MATH 839 (01) - Applied Regression Analysis

Applied Regression Analysis

Durham   Engineering&Physical Sciences :: Mathematics&Statistics
Credits: 3.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 10266
Statistical methods for the analysis of relationships between response and input variables: simple linear regression, multiple regression analysis, residual analysis model selection, multi-collinearity, nonlinear curve fitting, categorical predictors, introduction to analysis of variance, analysis of covariance, examination of validity of underlying assumptions, logistic regression analysis. Emphasizes real applications with use of statistical software. Students must have completed an introductory statistics course.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF

Times & Locations

Start Date End Date Days Time Location
8/30/2021 12/13/2021 MWF 8:10am - 9:30am KING S320


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