OPTIONS LS=75 NODATE;

/* A survey of IT managers was used to predict salaries for
beginning programmers, which may be related to these variables:
numempl: number of employees
margin:  profit margin
ipcost:  information processing cost
*/ 

DATA salaries;
   INPUT salary numempl margin ipcost;
   CARDS;
29.5  58  19.3999996  10.1400003
29.2999992  37  17.7000008  9.1800003
29.7999992  135  20.3999996  6.8400002
29.2000008  69  20.5  7.5900002
28.8999996  48  19.1000004  4.96
31.7000008  159  23.2999992  10.5200005
27.5  42  23.3999996  8.6099997
29.3999996  37  23.1000004  10.7200003
30.3999996  71  18.5  5.6500001
27.7000008  69  16.3999996  5.46
30.8999996  121  24.6000004  7.3699999
28.8999996  389  11  7.4000001
29.7000008  99  20.8999996  9.0500002
30.2999992  62  23  8.8100004
31.2999992  107  15.3000002  10.9399996
30  42  18.7999992  6.8400002
30  35  21  6.4499998
28.5  42  10.5  6.0599999
29.8999996  31  19.2999992  10.1999998
29.7000008  78  18  9.6000004
30.2000008  132  23.5  7.8800001
29.7000008  37  22.3999996  6.71
29.8999996  89  22.7999992  10.04
29  101  21.7000008  8.3900003
29.3999996  60  18  5.2399998
30.2999992  48  21.8999996  9.6000004
30.3999996  75  22.6000004  11.6300001
31.1000004  71  24.5  9.6499996
29.3999996  47  24.2000008  7.9400001
30.7000008  39  22.7000008  9.6700001
30.2000008  50  23.1000004  9.6599998
30.7000008  40  16.1000004  10.3100004
28.5  102  16.2000008  6.6700001
29  38  21.8999996  6.4499998
29.2000008  80  20.8999996  10.0699997
28.1000004  77  14  7.0599999
27.7000008  28  19.7999992  9.6999998
27.2999992  30  6.6999998  3.1600001
31.2999992  34  21.3999996  10.9099998
27.3999996  28  16  8.1899996
29.2999992  230  14.8999996  5.6999998
28.7000008  121  19.2999992  6.4200001
29.7000008  146  20.8999996  5.7399998
29.2999992  124  17.6000004  6.1300001
28.2999992  40  16.2999992  8.8599997
25.7000008  130  15.6000004  4.1100001
27.2000008  60  15.8999996  6.1300001
29.2000008  94  22.6000004  9.9499998
30.2000008  43  19.6000004  7.8299999
30.7000008  111  18.2000008  6.6999998
29.3999996  37  23  11.25
28.3999996  76  15.5  4.77
30.1000004  188  18.8999996  5.9400001
28.5  64  12.6000004  4.8099999
28.7999992  185  17.7000008  8.6599998
32.4000015  371  22.2999992  7.4499998
28.3999996  81  23.1000004  5.1399999
29.7000008  62  20.8999996  9.2600002
27  30  9.8000002  1.4400001
28.2000008  103  22.1000004  7.98
27.6000004  29  9.6999998  6.0900002
30.7000008  28  17.1000004  8.71
28.7000008  34  16.7999992  5.1100001
29.3999996  279  23.2000008  6.1999998
29.8999996  35  23.3999996  8.4200001
31.2999992  43  18.2999992  7.52
28.5  77  19  7.8499999

;
RUN;

PROC INSIGHT;RUN;
/* 
Obtain a scatterplot matrix of all four variables
using the SAS/INSIGHT facility:
Choose the WORK library.
Choose the SALARIES library.
Choose Analyze from the menu at the top
Choose scatterplot (Y X)
Highlight all four variables using shift-click.
Click them into both the Y area and X area at the right of
the Scatterplot box.  Click OK.
*/

PROC REG DATA=salaries;
   MODEL salary=numempl margin ipcost;
   comparemods: TEST margin=ipcost=0;
   /* The TEST statement compares these two models for mu(x1,x2,x3): 
      mu(x1,x2,x3) = b0 + b1x1 
      mu(x1,x2,x3) = b0 + b1x1 + b2x2 + b3x3 */
   *MODEL salary=numempl;  
   /* 2nd MODEL statement to reconcile the results of TEST statement */
   /* PROC REG permits multiple MODEL statements */
RUN;