Outcome 4: Multiple Regression: A real estate agency wishes to develop a regression model that can be used to predict th

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Outcome 4 Multiple Regression A Real Estate Agency Wishes To Develop A Regression Model That Can Be Used To Predict Th 1 (55.14 KiB) Viewed 27 times

Outcome 4 Multiple Regression A Real Estate Agency Wishes To Develop A Regression Model That Can Be Used To Predict Th 2 (50.94 KiB) Viewed 27 times

Outcome 4: Multiple Regression: A real estate agency wishes to develop a regression model that can be used to predict the sales prices of future homes it will list. In order to do so the agency collects data on the following: Regression Statistics Dependent: Home Sale Price Multiple R 0.995 R Square 0.980 Adjusted R Square 0.976 Standard Error 3.242 Observations 30 ANOVA Significance F DI MS F 350.866 Regression Residual Total 9.58E-08 S S 7373.952 73.557 7447.509 NN 2 7 9 3686.976 10.508 Coefficients Stat P-value Lower 95% Intercept Square feet Baths 29.347 0.056 8.834 Standar d Error 4.891 0.023 0.433 6.000 4.561 2.851 0.001 0.000 0.000 17.780 5.072 2.810 Y = Home Sale Price (in $1000) X1 = Home Size (in square feet) X2 - # of Bathrooms 1. Write the equation for linear regression [Y - bO + b1X: + b2 X2 + error] in terms of the variables and the estimated coefficients.

2. Interpret the value of adjusted R2 for the model. Comment on the goodness of fit of the model. 3. Use the coefficient estimates to describe the relationship between Square Feet area and Sale Price of a house; # of Baths and Sale Price (in the units given above). 4. Calculate the predicted sale price of a house with 3000 square feet and 3 baths. 5. Conduct a test of hypothesis using a = 0.05, for by, and b Compare the model t-stats for each independent variable against the critical t-value for a 2-sided test and determine if the variable is significant in explaining home price Ho: b = 0 HA: b*0 a. Sample size n- ii. Critical t-value or z-value = b. Use the t-stats from the Excel output to determine if you should accept or reject the Ho for b1 and 52 (include the t-stats from the Excel output in your answer) c. What conclusions can you draw about the significance of Home Size and # of Baths in determining the Sale Price of a home? Explain. (copy the questions below when answering each part]