Lecture 25. Regression diagnostics for the multiple linear regression model Dealing with influential observations for multiple linear regression Interaction variables. Assumptions of Multiple Linear Regression Model. Assumptions of multiple linear regression:
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[Distribution of residuals should not depend on
EDUC=median number of school years completed for persons 25 and older;
NONWHITE=percentage of 1960 population that is nonwhite;
HC=relative pollution potential of hydrocarbons (product of tons emitted per day per square kilometer and a factor correcting for SMSA dimension and exposure)
Residual plots look fine. No strong indication of nonlinearity or
Normality looks okay. One residual outlier, Lancaster.