Things we will done in Lab: 1. Correlation test for normality 2. Modified Levene’s test 3. Breusch Pagan Test 4. Lack of fit test for linear model 5. Durbin Watson Test 6. Box-Cox Transformation options ls=90 ps=55; data tree; input diameter height; newvar=_n_; cards; 18.9 20.0 15.5 16.8 19.4 20.2 20.0 20.0 29.8 20.2 19.8 18.0 20.3 17.8 20.0 19.2 22.0 22.3 23.6 18.9 14.8 13.3 22.7 20.6 18.5 19.0 21.5 19.2 14.8 16.1 17.7 19.9 21.0 20.4 15.9 17.6 27.5 21.4 20.3 19.2 22.9 19.8 14.1 18.5 10.1 12.1 5.8 8.0 20.7 17.4 17.8 18.4 11.4 17.3 14.4 16.6 13.4 12.9 17.8 17.5 20.7 19.4 13.3 15.5 22.9 19.2 16.6 18.8 15.5 16.9 13.7 16.3 ; /* plotting the data*/ proc gplot data=tree; plot height*diameter; run; /* regression of y on x with test for non-constant variance*/ proc reg data=tree; model height=diameter/clm cli dw; /* getting the residual and predicted values as a different data set*/ output out=new r=resid p=pred; run; /* residual analysis*/ proc univariate normaltest plot data=new; var resid; run; /* residual analysis another way*/ proc capability normaltest data=new; var resid; histogram; cdfplot; qqplot; run; /*diagnostic plots for equal equality of variance 1*/ proc gplot data=new; plot resid*pred; run; /*diagnostic plots for equal equality of variance 2*/ data new1; set new; sqres=resid*resid; proc gplot; plot sqres*pred; run; /*Normal probability plot directly*/ proc rank normal=blom data=new out=data2; ranks residr; var resid; proc gplot data=data2; plot resid*residr; run; /* correlation test for normality*/ proc corr ; var resid residr; run; proc sort data=new; by diameter; run; /* for Breusch-pagan test*/ proc model data=tree; parms b0 b1; height=b0+b1*diameter; fit height/white breusch=(1 diameter); run; /* modeified levene's test */ data levnew; set new; newvar1=_n_; if newvar1 < 19 then grp =1; else grp=2; run; proc glm data=levnew; class grp; model resid=grp; means grp/hovtest=bf; run; /* To find SSPE for lack of fit test, don’t use SSLF just use SSPE*/ proc sort data=tree; by diameter; run; proc rsreg; model height=diameter/lackfit; run; ods graphics on; proc transreg details data=tree ss2 plots=(transformation(dependent) obp); model BoxCox(height / convenient lambda=-2 to 2 by 0.05) = qpoint(diameter); run; ods graphics off; %boxcoxar(tree,height,lambdahi=5,lambdalo=-5,nlambda=55); run;