Regression Statistics Multiple R 0.751929782 R Square 0.565398397 Adjusted R Squ
ID: 3158881 • Letter: R
Question
Regression Statistics Multiple R 0.751929782 R Square 0.565398397 Adjusted R Square 0.561008482 Standard Error 60146.24913 Observations 101 ANOVA df SS MS F Significance F Regression 1 465924492728.572 465924492728.572 128.7948339 1.28565E-19 Residual 99 358139557172.418 3617571285 Total 100 824064049900.99 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -40629.73461 16930.10108 -2.399851863 0.018271542 -74222.72816 -7036.741054 -74222.72816 -7036.741054 X Variable- Sq Footage 87.39367876 7.700710543 11.34878116 1.28565E-19 72.11379836 102.6735592 72.11379836 102.6735592 Coefficient Correlation 0.751929782 Sum of listing price $14,049,200.00 ~y = 139,100.99 Sum of square footage 207713 ~x = 2,056.56436 Significance of Slope 87.39367876 T-Test 11.34878116 P-Value 1.28565E-19
Given this information, what would be the price for a house that is 2100 square feet? Please show work.
Explanation / Answer
The estimated regression equation is:
Price=-40629.73461+87.39367876 square feet
Substitute square feet with 2100 and compute the price.
Price=-40629.73461+87.39367876*2100
=142896.990786