/*
Residential sales prices .. from Problem 19 chapter14 of KKMN
pages 355-357.

A random sample of data were collected on residential sales in
a large city...
 
   sales price (in $1,000s)
   
   area (in hundreds of square feet)
   
   number of bedrooms
   
   total number of rooms
   
   age (in years), and 
   
   location (dummy variables defined as follows: 
   
      i_suburb = 0, o_suburb = 0 for intown; 
      i_suburb = 1, o_suburb = 0 for inner suburbs;
      i_suburb = 0, o_suburb = 1 for outer suburbs
      
for each house.

The data are contained inside the sas program. A sas permanent 
dataset is also available.

In the sas program, one categorical variable is computed and
added to the list, namely
  
      location = 0 intown
      location = 1 inner suburbs
      location = 2 outer suburbs.

This variable is also included in the sas permanent file.

*/

options ps=55 ls=75;
data sasuser.housepri;
input house price area bedrooms rooms age i_suburb o_suburb;
location = 1*i_suburb + 2*o_suburb; /* 0=intown 1=inner sub. 2 = 
outer sub. */
lines;
 1  84.0  13.8  3  7  10  1  0
 2  93.0  19.0  2  7  22  0  1
 3  83.1  10.0  2  7  15  0  1
 4  85.2  15.0  3  7  12  0  1
 5  85.2  12.0  3  7   8  0  1
 6  85.2  15.0  3  7  12  0  1
 7  85.2  12.0  3  7   8  0  1
 8  63.3   9.1  3  6   2  0  1
 9  84.3  12.5  3  7  11  0  1
10  84.3  12.5  3  7  11  0  1
11  77.4  12.0  3  7   5  1  0
12  92.4  17.9  3  7  18  0  0
13  92.4  17.9  3  7  18  0  0
14  61.5   9.5  2  5   8  0  0
15  88.5  16.0  3  7  11  0  0
16  88.5  16.0  3  7  11  0  0
17  40.6   8.0  2  5   5  0  0
18  81.6  11.8  3  7   8  0  1
19  86.7  16.0  3  7   9  1  0
20  89.7  16.8  2  7  12  0  0
21  86.7  16.0  3  7   9  1  0
22  89.7  16.8  2  7  12  0  0
23  75.9   9.5  3  6   6  0  1
24  78.9  10.0  3  6  11  1  0
25  87.9  16.5  3  7  15  1  0
26  91.0  15.1  3  7   8  0  1
27  92.0  17.9  3  8  13  0  1
28  87.9  16.5  3  7  15  1  0
29  90.9  15.0  3  7   8  0  1
30  91.9  17.8  3  8  13  0  1
;
run;