* Required macros: 'regr', 'diff';

* this SAS code shows how to do calculations for regression estimators using SAS as a 
calculator.  Note that there are other ways to use SAS, like Proc REG to perform these
calculations directly;

data ex6_9 ;
  input student achieve final @@ ;
  cards ;
  1 39 65   2 43 78    3 21 52 
  4 64 82   5 57 92    6 47 89 
  7 28 73   8 75 98    9 34 56
  10 52 75 
   ;
run;

proc sgplot ;
  scatter x=achieve y=final;
run ;

proc means ;
  var final achieve;
run;

data regcalc ; set ex6_9 ;
  bnumerator = (achieve -46)*(final -76) ;
  bdenominator = (achieve -46)**2 ;
run;

proc means sum data = regcalc ;
  var bnumerator bdenominator ;
run ;
 
data msecalc ; set ex6_9 ;
  finalhat = 76 + .7656*(achieve -46) ;
  sqerror = (final -finalhat)**2 ;
run;

proc means sum data = msecalc ;
  var sqerror ;
run ;

* Using PROC REG

proc reg plots=(diagnostics residuals) data = ex6_9 ;
 model final = achieve ;
run;

* Using SAS as a calculator for the difference estimator; 

data ex6_10 ;
 input sample auditvalue bookvalue @@ ;
 d = auditvalue -bookvalue ;
 cards ;
  1 9 10   2 14 12  3 7 8   4 29 26 
  5 45 47  6 109 112  7 40 36   8 238 240 
  9 60 59   10 170 167 
   ;
run;

proc splot data = ex6_10 ;
  scatter x=bookvalue y=auditvalue;
run;

proc means data = ex6_10 ;
  var auditvalue bookvalue ;
run ;

data msecalc6_10;
  set ex6_10 ;
  sqerror = (d - .4)**2;
run;

proc means sum data = msecalc6_10 ;
  var sqerror ;
run ;


* Make sure you have run the required macros;

 
%regr(sample=ex6_9,npop=488,response=final,param=mean,x=achieve,mu_x=52) ;

%diff(sample=ex6_10,npop=180,response=auditvalue,param=mean,x=bookvalue,mu_x=74) ;