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Unformatted text preview: Summary of Regression Diagnostics Regression diagnostics are used after fitting to check if a fitted mean function and assumptions are consistent with observed data. The basic statistics: the residuals e i = y i y i 1. Check to see if the linear mean function is adequate Plot : e i versus y i Remedy: add x 2 terms into the model 2. Check to see if the constant variance assumption is valid Plot : e i versus y i Remedy: variance stabilizing transformations 3. Sometimes, we assume that the residuals have normal distribution Plot: QQ plot of e i to check the normality assumption. Chapter 9 Outliers and Influence Outlier: cases that do not follow the same model as the rest of the data. Mean Shift Outlier Model: E ( Y  X = x j ) = x j T j i E ( Y  X = x i ) = x i T + An Outlier Test: 1. Delete i th case, n1 cases left in the reduced data....
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This note was uploaded on 12/12/2010 for the course STAT 425 taught by Professor Ma,p during the Fall '08 term at University of Illinois, Urbana Champaign.
 Fall '08
 Ma,P
 Statistics

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