data sportscars; set sashelp.cars; if type = "Sports"; run; proc print data=sportscars;run; data sportscars2 (keep= horsepower mpg_city shortname); set sportscars; id=find(strip(model), " "); put model id; if (id > 0) then shortname=substr(model, 1, id); run; proc print data=sportscars2;run; proc sort data=sportscars2; by shortname; run; proc means data=sportscars2; by shortname; var horsepower mpg_city; output out=sasuser.sportsCarsMean mean = HP MPG; run; proc print data=sasuser.sportsCarsMean;run; title 'Linear Regression'; proc reg data=sasuser.sportsCarsMean outest=sportscarfit_est; model hp=mpg; output out=sasuser.sportsCarMeanFit lcl=lower ucl=upper lclm=lowermean uclm=uppermean predicted=predict; run; proc sort data=sasuser.sportsCarMeanFit; by mpg; run; proc print data=sasuser.sportsCarMeanFit; run; /* */ ods listing sge=on style=Default; ods graphics on / reset width=400px imagename='CarsLabels'; proc sgplot data=sasuser.sportsCarMeanFit; band x=mpg upper=uppermean lower=lowermean / name='band' legendlabel='Confidence'; scatter x=mpg y=hp / dataLabel=shortname name='plot'; series x=mpg y=predict / name='predict' legendlabel='Predicted'; xaxis grid; yaxis grid; keylegend 'predict' 'band' / across=1 location=inside position=TOPRIGHT; run;