Question

A random sample of 22 residential properties was used in a regression of price on nine different independent variables. The variables used in this study were as follows:

PRICE 5 selling price (dollars)
BATHS 5 number of baths (powder room 5 1/2 bath)

BEDA 5 dummy variable for number of bedrooms (1 5 2 bedrooms, 0 5 otherwise) BEDB 5 dummy variable for number of bedrooms (1 5 3 bedrooms, 0 5 otherwise) BEDC 5 dummy variable for number of bedrooms (1 5 4 bedrooms, 0 5 otherwise)

CARA 5 dummy variable for type of garage (1 5 no garage, 0 5 otherwise) CARB 5 dummy variable for type of garage (1 5 one-car garage, 0 5 otherwise)

AGE 5 age in years
LOT 5 lot size in square yards

DOM 5 days on the market

Row     PRICE   BATHS   BEDA    BEDB    BEDC    CARA    CARB    AGE     LOT     DOM     
1       25750   1.0     1       0       0       1       0       23      9680    164     
2       37950   1.0     0       1       0       0       1       7       1889    67      
3       46450   2.5     0       1       0       0       0       9       1941    315     
4       46550   2.5     0       0       1       1       0       18      1813    61      
5       47950   1.5     1       0       0       0       1       2       1583    234     
6       49950   1.5     0       1       0       0       0       10      1533    116     
7       52450   2.5     0       0       1       0       0       4       1667    162     
8       54050   2.0     0       1       0       0       1       5       3450    80      
9       54850   2.0     0       1       0       0       0       5       1733    63      
10      52050   2.5     0       1       0       0       0       5       3727    102     
11      54392   2.5     0       1       0       0       0       7       1725    48      
12      53450   2.5     0       1       0       0       0       3       2811    423     
13      59510   2.5     0       1       0       0       1       11      5653    130     
14      60102   2.5     0       1       0       0       0       7       2333    159     
15      63850   2.5     0       0       1       0       0       6       2022    314     
16      62050   2.5     0       0       0       0       0       5       2166    135     
17      69450   2.0     0       1       0       0       0       15      1836    71      
18      82304   2.5     0       0       1       0       0       8       5066    338     
19      81850   2.0     0       1       0       0       0       0       2333    147     
20      70050   2.0     0       1       0       0       0       4       2904    115     
21      112450  2.5     0       0       1       0       0       1       2930    11      
22      127050  3.0     0       0       1       0       0       9       2904    36      

Using the 9 variable model, give a 95% prediction interval for a house that has 2 baths, 3 bedrooms, 1 car garage, is 10 years old, has 2000 square feet and has been on the market for 60 days.

Please show minitab step by step!

Answer 1

Enter the data into Minitab.

Go to STAT > Regression > Regression > Fit Regression Model.

Enter the variables as follows:

Click OK.

Go to STAT > Regression > Regression > Predict.

Enter the variables as given for the prediction interval.

Enter upto the end and Click OK.

Click OK.

The output is:

The 95% prediction interval for a house that has 2 baths, 3 bedrooms, 1 car garage, is 10 years old, has 2000 square feet and has been on the market for 60 days is between 7301.91 and 92036.4.