You are working for the real estate company and you are tasked to build a model that predicts the property value in thousands of USD based on a set of factors. The potential factors include: • square footage (SqFt), • lot size (in thousands of square feet), • number of bathrooms, • whether the house is in a gated community (1 = yes, 0 = no) = | = Below is the partial computer output for a multiple linear regression model used to predict the price of a house in thousands of $. с D E F A B 1 SUMMARY OUTPUT 2 3 Regression Statistics 4 Multiple R 5 R Square 6 Adjusted R Square 0.938693133 7 Standard Error 22.67365547 8 Observations 9 10 ANOVA 11 df 12 Regression 13 Residual 25 MS F Significance F SS 230329.9324
25 243182.2987 t Stat P-value 13 Residual 14 Total 15 16 17 Intercept 18 SqFt 19 LotSize 20 Baths 21 Gated? Lower 95% -91.20253902 0.142131492 Coefficients -22.06508569 0.177985617 5.904504635 13.17656434 -0.129883323 Standard Error 33.56939021 0.017408815 1.611883763 10.28255457 8.449433339 -8.000753228 -17.53181703 What price can be expected for a hourse not in a gated community, on a lot of 6,500 SqFt, total house footage of 2,000 SqFt, and has 5 bathrooms? none of the listed values ООООО $408,733.00 $438,168.21 $408.733 $35,800,310 $438.17
You are working for the real estate company and you are tasked to build a model that predicts the property value in thou
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You are working for the real estate company and you are tasked to build a model that predicts the property value in thou
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