A company has recorded data on a sample of real estate listings from Waltham, MA. The variables are: PRICE -- List price, thousands of dollars
SQFT -- Square footage
BEDS -- Number of bedrooms
BATHS -- Number of bathrooms
HWY -- A dummy variable (1 = close to highways; 0 = far from highways).
Use Excel's Regression tool to answer the following questions:
PRICE SQFT BEDS BATHS HWY
713 2400 3 3 0
645 2524 3 2 1
625 2732 4 2.5 1
585 1947 3 1.5 0
583 2224 3 2.5 0
540 1488 3 1.5 0
511 1752 3 1.5 0
463 1714 3 2 1
435 1500 3 1.5 1
402 1152 3 1 1
380 1272 3 1 1
368 1272 3 1 1
356 1431 2 2 1
330 1465 3 1 0
308 850 1 1 0
Fill in Multiple Blanks. For all numerical answers, show two (2) digits to the right of the decimal point, for example, 1.00, 1.20, 1.22. Apply the appropriate rounding rule if necessary. Hint: You can use the "Format Cell" option in the Regression output so that it shows two digits after the decimal point. Excel will automatically round the values up or down, if necessary.
1. The estimated regression line is (enter the estimated coefficients in the appropriate space):
PRICEhat = Blank 1 + Blank 2 SQFT + Blank 3 BEDS + Blank 4 BATHS + Blank 5 HWY
2. On average, a house with 4 bedrooms will be Blank 6 thousand dollars Blank 7 (cheaper, more expensive) than a house with 2 bedrooms, ceteris paribus.
3. On average, a house located close to highways will be Blank 8 thousand dollars Blank 9 (cheaper, more expensive) than a house located far from highways, ceteris paribus.
4. Predict PRICE for a house with square footage of 1960, 2 bedrooms and 2.5 bathrooms, which is located far from highways. PRICEhat = Blank 10 (in thousands of dollars).
5. At 90% confidence, SQFT Blank 11 (is, is not) significantly related to PRICE.
6. At 90% confidence, BEDS Blank 12 (is, is not) significantly related to PRICE.
7. At 90% confidence, BATHS Blank 13 (is, is not) significantly related to PRICE.
8. At 90% confidence, HWY Blank 14 (is, is not) significantly related to PRICE.
9. True or false? At 90% confidence, a significant relationship exists between PRICE and the set of all the independent variables included in the regression model (SQFT, BEDS, BATHS, and HWY). Blank 15 (true, false).
10. True or false? About 85% of the variability in PRICE is explained by the set of all the independent variables included in the regression model (SQFT, BEDS, BATHS, and HWY), and about 15% of the variability in PRICE is explained by the other factors not included in the regression. Blank 16 (true, false).