Question: Regression Statistics Multiple R 0.53 R Square 0.28 Adjusted R Square 0.28 Standard Error 191.66 Observations 98 ANOVA df SS MS F Significance F Regression

Regression Statistics
Multiple R 0.53
R Square 0.28
Adjusted R Square 0.28
Standard Error 191.66
Observations 98
ANOVA
df SS MS F Significance F
Regression 1 1403819.33 1403819.33 38.22 1.54E-08
Residual 96 3526382.81 36733.15
Total 97 4930202.14
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 244.62 54.55 4.48 2.03E-05 136.34 352.90 136.34 352.90
lot 551.73 89.25 6.18 1.54E-08 374.58 728.89 374.58 728.89
  1. According to the coefficients from this regression, what is the equation you would use to predict the price of a home?
  2. How much of the variation in home price is explained by the variation in lot size, and which value from the output did you use to determine that?
  3. If a house lot size decreases by 0.5 acres, what will be the change in home price according to this regression?

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