OUTPUTNow some fancy graphs for illustration …/* file: preg-nitrofen-28jan04.doc directory: \Classes\Spring ‘04\ contents: polynomial regression example*/libname class 'Z:\baileraj\Classes\Fall 2003\sta402\data’;/* creates a permanent dataset with the nitrofen data */data nitrofen; infile 'M:\public.www\classes\sta402\SAS-programs\ch2-dat.txt' firstobs=16 expandtabs missover pad ; input @9 animal 2. @17 conc 3. @25 brood1 2. @33 brood2 2. @41 brood3 2. @49 total 2.; conc2 = conc*conc; * construct squared concentration; conc_adj = conc – 160; * rescale concentration; conc_adj2 = conc_adj*conc_adj;label animal = animal ID number;label conc = Nitrofen concentration;label brood1 = number of young in first brood;label brood2 = number of young in 2nd brood;label brood3 = number of young in 3rd brood;*label total = total young produced in three broods;proc print data= nitrofen; run;options formdlim=”-“ nodate;title “Response=Total Young and Predictors = nitrofen conc (scaled)”;proc reg; model total = conc conc2; model total = conc_adj conc_adj2;run;OUTPUT Response=Total Young and Predictors = nitrofen conc (scaled) 7 The REG Procedure Model: MODEL1 Dependent Variable: total Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 2 4902.67799 2451.33900 157.27 <.0001 Error 47 732.60201 15.58728 Corrected Total 49 5635.28000 Root MSE 3.94807 R-Square 0.8700 Dependent Mean 22.88000 Adj R-Sq 0.8645 Coeff Var 17.25556 Parameter Estimates Parameter StandardVariable Label DF Estimate Error t Value Pr > |t| Intercept Intercept 1 31.45773 1.17926 26.68 <.0001 conc Nitrofen concentration 1 0.03380 0.01794 1.88 0.0658 conc2 1 -0.00037868 0.00005558 -6.81 <.0001------------------------------------------------------------------------------------------------- Response=Total Young and Predictors = nitrofen conc (scaled) 8 The REG Procedure Model: MODEL2 Dependent Variable: total Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 2 4902.67799 2451.33900 157.27 <.0001 Error 47 732.60201 15.58728 Corrected Total 49 5635.28000 Root MSE 3.94807 R-Square 0.8700 Dependent Mean 22.88000 Adj R-Sq 0.8645 Coeff Var 17.25556 Parameter Estimates Parameter Standard Variable Label DF Estimate Error t Value Pr > |t| Intercept Intercept 1 27.17148 0.86967 31.24 <.0001 conc_adj 1 -0.08738 0.00513 -17.04 <.0001 conc_adj2 1 -0.00037868 0.00005558 -6.81 <.0001Now some fancy graphs for illustration …ODS RTF file='D:\baileraj\Classes\Fall 2003\sta402\SAS-programs\week5-fig2.rtf';/* SYMBOL = defines characteristics of plotted symbols */proc gplot data=class.nitrofen;title h=1.5 'A plot of the number of C. dubia produced at different Nitrofen concentrations';title2 h=1 '[mean +/- 2SD is plotted for each concentration]'; symbol1 interpol=STD2T /* plots +/- 2 SD from the mean at each conc */ /* T= add top and bottom to each 2 SD diff */ value=dot; plot total*conc / hminor=1 /* hminor=# tick markets before x values */ haxis=0 to 350 by 50;run;ODS RTF CLOSE;proc means data= nitrofen; class conc; var total; output out=nitromean mean=n_mean stddev=n_sd;run;proc print; run; Obs conc _TYPE_ _FREQ_ n_mean n_sd 1 . 0 50 22.88 10.7241 2 0 1 10 31.40 3.5963 3 80 1 10 31.50 3.2745 4 160 1 10 28.30 2.3594 5 235 1 10 17.20 5.9029 6 310 1 10 6.00 3.7118ODS RTF file='D:\baileraj\Classes\Fall 2003\sta402\SAS-programs\week5-fig3.rtf';proc gplot data=nitromean;title h=1.5 'Plot of mean number of C. dubia young produced at different Nitrofen concentrations';title2 h=1 '[bubble area proportional to std dev.]'; bubble n_mean*conc=n_sd / bsize=15; /* bsize helps resize bubble for display */ run;ODS RTF CLOSE;G3D figureslibname class 'D:\baileraj\Classes\Fall 2003\sta402\data’; data new; set class.nitrofen; retain conc; brood=1; young=brood1; output; brood=2; young=brood2; output; brood=3; young=brood3; output; keep conc brood young; data new2; set new; jconc = conc + (10-20*ranuni(0)); jbrood = brood + (1-2*ranuni(0)); run;ODS RTF file='D:\baileraj\Classes\Fall 2003\sta402\SAS-programs\week5-fig7.rtf';proc g3d data=new2;title h=1 ‘Scatter plot of # young by conc. and brood (jittered)’; scatter jconc*jbrood=young / xticknum=2 yticknum=2; run;quit;ODF RTF CLOSE;proc means data=new; class conc brood; var young; output out=new3 mean=ymean;run;ODS RTF file='D:\baileraj\Classes\Fall 2003\sta402\SAS-programs\week5-fig8.rtf';proc g3d data=new3;title h=1 'Surface plot of mean # young by conc. and brood';plot conc*brood=ymean / xticknum=2 yticknum=2 tilt=80; run; quit;ODS RTF
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