A local real estate developer wishes to study the relationship between the size
ID: 3130833 • Letter: A
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.
Evaluate in excel and add directions on how and which formulas you used. Thank you so much!
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 6Explanation / Answer
Dear Mr. Bostick explaining,
After running the multiple linear regression on the data provided by you, it turns out to be that the model is significant. Please have a look at the following output.
Based on this output we can write the regression model as -
Square Foot = 1650.15 + 4.46(Income) + 431.33 (Family Size) -156.14 (Senior Parent) - 67.07(Education)
The regression is overall significant as the F value is much higher than the critical F-value for the overall significance test of model (it is there in the output table).
The R-square value is approximately 0.93, which indicates this is a good model.
The variable "Family Size" is most effective in deciding the area of house a person would be looking for which is also logical. And I think that the presence of senior parent doesn't affect much on the area of house to be purchased. And of course a person with high income will look for larger area.
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 770.3346891 2529.957359 Income (000s) 4.464850481 4.564738239 0.978117528 0.372937182 -7.269182722 16.19888368 Family Size 431.3283167 125.6296288 3.433332731 0.018568565 108.3870748 754.2695586 Senior Parent -156.1360569 212.3396625 -0.73531273 0.495170804 -701.9725363 389.7004225 Education -67.07422456 29.46766479 -2.276197488 0.071879163 -142.8232684 8.674819286Related Questions
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