In: Statistics and Probability
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.