*SAS code for the final exam review problems;

********************************************;
* CH01PR22.DAT ;

**  1.22  ;

data hard;
infile 'CH01PR22.DAT'; 
input Y X;
run;
proc print;run; 

data new;
input Y X;
datalines;
. 40
;
run;
proc print;run;

data hard2;
set hard new;
run;
proc print;run;

proc reg data=hard2;
model Y = X / p;
run;

** 2.7 ;
proc reg data=hard2;
model Y = X / clb alpha=0.01;
run;

** 2.16 ;
data new2;
input Y X;
datalines;
. 30
;
run;
proc print;run;

data hard3;
set hard new2;
run;
proc print;run;

proc reg data=hard3;
model Y = X / p clm cli alpha=0.02;
run;

** 2.26;
proc reg data=hard3;
model Y = X ;
run;

** 3.6 ;
proc reg data=hard;
model Y = X ;
output out=hardres p=pred r=res;
run;
proc print data=hardres; run;

proc univariate data=hardres plot;
var res;
qqplot res / normal ;
run;

proc gplot data=hardres;
plot pred*res X*res;
run;

** 4.9 (a) ;

data new3;
input Y X;
datalines;
. 20
. 30
. 40
;
run;
proc print;run;

data hard4;
set hard new3;
run;
proc print;run;

proc reg data=hard4;
model Y = X / p clm ;
run;

data tc;
c=tinv(0.9833,14);
run;
proc print;run;
 
***********************************************************;
** CH06PR15.DAT ;

** 6.15 ;

data patient;
infile 'CH06PR15.DAT';
input Y X1 X2 X3;
run;
proc print;run;

proc gplot data=patient;
plot Y*X1 Y*X2 Y*X3 X1*X2 X1*X3 X2*X3;
run;

proc corr data=patient noprob; run; 

proc reg data=patient;
model Y=X1 X2 X3;
output out=ptres p=pred r=res;
run;

data ptall;
set patient ptres;
X12=X1*X2;
X23=X2*X3;
X13=X1*X3;
run;
proc print;run;

proc univariate data=ptres plot;
var res;
qqplot res / normal ;
run;

proc gplot data=ptall;
plot res*pred res*X1 res*X2 res*X3 res*X12 res*X23 res*X13;
run;

** 6.16 ;

proc reg data=patient;
model Y=X1 X2 X3;
run;

data tc2;
c=tinv(0.9833,42);
run;
proc print;run;

** 6.17 ;

data pnew;
input Y X1 X2 X3;
datalines;
. 35 45 2.2
;
run;

data patient2;
set patient pnew;
run;
proc print;run;

** 6.17(a) ; 

proc reg data=patient2;
model Y=X1 X2 X3 / p clm alpha=0.10;
run;
 
** 6.17 (b) ;

proc reg data=patient2;
model Y=X1 X2 X3 / p cli alpha=0.10;
run;

** 7.5 ;

proc reg data=patient;
model Y = X2 X1 X3 / ss1;
dropX3: test X3;
run;

** 7.14 (a) ;

proc reg data=patient;
model Y = X1 / pcorr1;
run;

proc reg data=patient;
model Y = X2 X1 / pcorr1;
run;

proc reg data=patient;
model Y = X3 X2 X1 / pcorr1;
run;

** 9.9 ;

proc reg data=patient;
model Y = X1 X2 X3 / selection = cp aic ADJRSQ;
run;

proc reg data=patient;
model Y = X1 X2 X3 / selection = forward;
run;

** 10.11;

data chap10;
input Y X1 X2 X3;
datalines;
. 30 58 2.0
;
proc print;run;

data patient10;
set patient chap10;
run;
proc print;run;

proc reg data=patient10;
model Y = X1 X2 X3 / r influence;
run;


***************************************;
** Merge CH08PR16.txt and CH01PR19.DAT;

data set2;
infile 'CH08PR16.txt';
input X2;
run;
proc print;run;

data set1;
infile 'CH01PR19.DAT';
input Y X1;
run;
proc print;run;

data both;
merge set1 set2;
run;
proc print;run;

** 8.16 ;

proc reg data=both;
model Y = X1 X2;
output out=bothres r=res;
run;

symbol1 v=1 c=black;
symbol2 v=0 c=red;
proc gplot data=bothres;
plot res*X1=X2;
run;

** 8.20 ;

data both2;
set both;
X12=X1*X2;
run;
proc print;run;

proc reg data=both2;
model Y = X1 X2 X12;
run;

*****************************************************;
** 16.10 17.11 18.7 ;

data cat;
input Y A $ B $;
datalines;
23 y o
25 y o 
21 y w
22 y o
21 y w
22 y o
20 y w
23 y o
19 y w
22 y o 
19 y w
21 y w
28 m o
27 m w 
27 m w
29 m o
26 m w
29 m o
27 m w
30 m o
28 m o
27 m w
26 m w
29 m o
23 e o
20 e w 
25 e o
21 e w
22 e o
23 e o
21 e o
20 e w
19 e w 
20 e w
22 e o
21 e w
;
run; 
proc print;run;

** 16.10 ;
proc gplot data=cat;
plot Y * A;
run;

proc glm data=cat;
class A B;
model Y = A ;
means A/tukey bon;
output out=catres r=res p=pred;
run;

** 17.11;

** (a) ;
proc sort data=cat;
by A;
run;

proc means data=cat;
var Y;
by A;
output out=catmean mean=Amean;
run;
proc print data=catmean;run;

proc gplot data=catmean;
plot Amean*A;
run;

** (b) ;
proc glm data=cat;
class A;
model Y=A;
means A/t clm alpha=0.01;
run;

** (c) ;
proc glm data=cat;
class A;
model Y=A;
means A/lsd cldiff alpha=0.01;
run;

** (e,f) ;

proc glm data=cat;
class A;
model Y=A;
means A/tukey bon cldiff alpha=0.1;
run;

** (d) ;
proc glm data=cat;
class A;
model Y=A;
contrast '2*u2-u1-u3' A -1 2 -1;
estimate '2*u2-u1-u3' A -1 2 -1;
run;

** 18.7 ;

proc glm data=cat;
class A B;
model Y=A B A*B;
output out=factor r=res;
run;
proc print data=factor;
run;

proc gplot data=factor;
plot res*A=B;
run;

proc univariate data=factor plot;
var res;
qqplot res/normal;
run;

proc glm data=cat;
class A B;
model Y=A B A*B;
means A B A*B;
run;