(15 points) A realtor wanted to find a model that relates the asking price of a

Question

(15 points) A realtor wanted to find a model that relates the asking price of a house to the square footage, number of bedrooms, and number of bathrooms. The following data are from houses in Greensville, SC. The response (Y) is the asking price (in thousands of dollars). The independent variables are: X1-square footage, X2-number of bedrooms, and X3-number of bathrooms. Perform the complete appropriate analysis (i.e., choose the best model for asking price of houses in Greensville, SC and check all assumptions). X1 3632 4889 3000 3669 2800 3600 2800 2257 2000 2455 2250 2938 2399 X246 5 445 5 33 3 3 33 X3 2.5 5 3.5 3.5 3 3.5 25 33 2.5 222 Y ! 419 399 395 379 359 349 320 299 295 290 285 269 260

Explanation / Answer

here we use multiple linear regression to predict price (y) from the variables x1,x2,x3

the regresstion eqution is y=170.096+0.018*x1+20.741*x2+12.192*x3

SUMMARY OUTPUT Regression Statistics Multiple R 0.658802083 R Square 0.434020184 Adjusted R Square 0.245360245 Standard Error 55.83929032 Observations 13 ANOVA df SS MS F Significance F Regression 3 21519.45521 7173.152 2.300542 0.14589734 Residual 9 28062.23709 3118.026 Total 12 49581.69231 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 170.0964047 66.52098059 2.557034 0.030837 19.61549232 320.5773 X Variable 1 0.017722097 0.035000269 0.506342 0.624787 -0.061454013 0.096898 X Variable 2 20.74101736 28.19670389 0.735583 0.480714 -43.04435817 84.52639 X Variable 3 12.19222775 31.29161552 0.389632 0.705868 -58.59432429 82.97878

Related Questions

Navigate

• Browse (All)
• Browse #
• Subjects

---

---

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.