REGRESSION ANALYSIS STAT 533

 
 
 

Topic REGRESSION ANALYSIS  533 Stat No of
Weeks
Contacthours
Introduction to Regression analysis – Assumptions underlying a simple linear Regression. Stufy of Residual plots 2 6
Test of linearity of the model, ANOVA,  Lack of Fit test
 
2 6
Confidence interval of mean Response. Prediction interval of a new observation. Interval estimation of  regression parameters
Multiple Comparison tests.
3 9
Regression Analysis using Matrix method. Multiple linear Regression. Second order regression.
 
3 9
linear Regression with indicator variables, Piece-wise regression, Logistic Regression.
 
3 9
Multicollinearity Problems in regression and some solutions – Ridge ression, Robust regression etc.  Detecting outliers, VIF, Cook’s distance
 
2 6

 
Required Text(s)
 
 

  • Applied Linear Regression Models by John Neter, William Wasserman and Michael Kutner,  Richard D. Irwin Inc. Illinois. {latest available ed.}
  •  

 
 
 

  • Translation of the text book .KSU
  • Applied Linear Regression Analysis by Norman Draper and Harry Smith, Wiley
  • Theory and Application of the Linear Model by Franklin A. Graybill, Duxbury Press.
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