Applied Regression Analysis
Credit Hours:
3 hours
Applied methods in regression analysis with implementation in R. Topics include linear regression with mathematical examination of model assumptions and inferential procedures; multiple regression and model building, including collinearity, variable selection and inferential procedures; ANOVA as regression analysis; analysis of covariance; diagnostic checking techniques; generalized linear models, including logistic regression.
Prerequisites:
Undergraduate Prerequisite: (STAT 4210 or STAT 4110H) and (MATH 2250 or MATH 2250E) and (STAT 2010 or STAT 2360-2360L)
Graduate Prerequisite: STAT 6210 or STAT 6310 or STAT 6315 or permission of department
Semester Offered:
Fall
Spring
Summer
Level: