A local real estate developer wishes to study the relationship between the size

Question

A local real estate developer wishes to study the relationship between the size of home a client will purchase (in square feet) and other variables. Possible independent variables include the family income, family size, whether there is a senior adult parent living with the family (1 for yes, 0 for no), and the total years of education beyond high school for the husband and wife. The sample information is contained in the file RealEstateChapter14. Mr. Robert Bostick is a real estate broker who asked you to produce a model to predict the square footage a potential buyer would purchase. Based on the data in the file RealEstateChapter14, is the overall regression model significant if = 0.05? Write a memorandum to Mr. Bostick explaining if the model is significant and if so, which variables make a difference in the size of home a client might purchase. Do you calculations in Excel and title the file

Real Estate Family Square Feet Income (000s) Family Size Senior Parent Education Square Feet Size of home purchased 1 2,771 46.9 3 0 4 Income (000s) Family Income 2 2,380 68.4 2 1 6 Family Size Number of individuals in the immediate family 3 3,283 104.5 3 0 7 Senior Parent 1 if a senior parent lives in the household, 0 if not 4 3,119 94.1 3 1 0 Education Years of education after high school 5 3,217 50.6 3 0 2 6 2,595 114 3 1 10 7 4,480 125.4 6 0 6 8 2,520 83.6 3 0 8 9 4,200 133 5 0 2 10 2,800 95 3 0 6 +

Explanation / Answer

Following is the regression output generated by the excel:

Since p-value of F test 0.0037, in ANOVA table, is less than 0.05 so the overall regression model is significant.

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Following table shows the coeffcients and p-value of the coefficients:

Since p-value of the family size and intercept is less than 0.05 so variable family size make a significant difference on the model.

SUMMARY OUTPUT Regression Statistics Multiple R 0.966550317 R Square 0.934219516 Adjusted R Square 0.881595129 Standard Error 242.1415833 Observations 10 ANOVA df SS MS F Significance F Regression 4 4163519.768 1040879.942 17.75259659 0.003701774 Residual 5 293162.7317 58632.54635 Total 9 4456682.5 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 1650.146024 342.2615545 4.821301144 0.004792953 770.3346894 2529.957359 Income (000s) 4.464850481 4.564738239 0.978117528 0.372937182 -7.269182718 16.19888368 Family Size 431.3283167 125.6296288 3.433332731 0.018568565 108.3870749 754.2695585 Senior Parent -156.1360569 212.3396625 -0.73531273 0.495170804 -701.9725361 389.7004223 Education -67.07422456 29.46766479 -2.276197488 0.071879162 -142.8232684 8.674819259

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