/* SAS Example 3: Fortune Magazine Example cont.                     */

/* Fortune Magazine published data on the worlds largest industrial
   corporations. Information was given on sales, profits, assets,
   stockholders' equity, and number of employees. Listed here are the
   data for a sample of 12 of these companies for four variables. Use
   the data to determine the equation of the multiple regression model
   to predict profits by revenue, assets and number of employees.
   Revenue, profits and assets are given in millions of dollars.     */

/* Since we saw that there was a problem with highly correlated
   predictor variables when we initially ran the model, we will try
   to narrow down our choice of predictor variables with several
   model refining techniques.                                     */

OPTIONS PS=52;
OPTIONS LS=78;
OPTIONS NODATE;
OPTIONS PAGENO=1;

DATA FORTUNE;
   INPUT COMPANY $ 1-30 PROFITS ASSETS EMPLOYEES REVENUES;
   CARDS;
      Nestle (Switzerland)      2377.8   34562.6  212687  41625.7
      Hitachi (Japan)           1146.7  105257.5  331673  76430.9
      Renault (France)           655.5   42357.4  138279  32188.0
      Rhone-Poulenc (France)     547.7   22947.1   81582  15559.5
      Volvo (Sweden)            1714.9   18652.9   60115  20204.0
      Petrofina (Belgium)        324.9   10868.2   14013  11399.1
      Dow (United States)        931.0   26545.0   53700  20015.0
      Pohang (South Korea)       474.9   15676.7   22891   9064.1
      Indian Oil (India)         326.6    5807.3   34729   8235.7
      Sandoz (Switzerland)      1268.7   14935.1   60304  11611.1
      Raytheon (United States)   596.9    7395.4   60200  10012.9
      Akzo Nobel (Netherlands)   647.5   10364.1   70400  12206.9
      ;
   RUN;

   PROC PRINT DATA=FORTUNE;
      TITLE 'Industrial Corporation Data';
   RUN;

   PROC REG;
      TITLE 'Stepwise Choice of Model To Predict Profits';
      MODEL PROFITS = ASSETS EMPLOYEES REVENUES/SELECTION=STEPWISE
                                                   SLE=.20 SLS=.10;
   RUN;