(House Selling Price) The data below show the selling price, square footage, bed

Question

(House Selling Price) The data below show the selling price, square footage, bedrooms, and age of houses that have sold in a neighborhood in the last six months Sguare footage Bedrooms Sellin rice Age 64,000 1,670 59,000 1,339 61,500 1,712 1,840 79,000 87,500 2,300 2,234 92,500 95,000 2,311 2,377 113,000 115,000 2,736 138,000 2,500 142,500 2,500 144,000 2,479 145,000 2,400 147,500 3,124 144,000 2,500 155,500 4,062 165,000 2,854 Develop seven regression models as below using the corresponding Excel data. Mode Y selling price, X1 square footage (House Selling Price Model 1 Data) (Model 2) selling price, X2E bedrooms (House Selling Price Model 2 Data) (Model 3) Y selling price, X3 age (House Selling Price Model 3 Data) (Model 4) Y selling price, X1 square footage, X2 bedrooms (House Selling Price Model 4 Data) (Model 5) Y selling price, X1 square footage, X3 age (House Selling Price Model 5 Data) (Model 6) Y selling price, X2 bedrooms, X3 age (House Selling Price Model 6 Data) Mode Y selling price, X1 square footage, X2 bedrooms, X3 age ouse Selling Price Model 7 Data House Selling Price is the best for predicting the selling price of a house in this neighborhood. A. Model 3 B. Model 7 C. Model 6 o D. Model 2 E. Model 4 o F. Model 5 G. Model 1 25 19

Explanation / Answer

Model 4 has highest R^2 which is 0.771575538045342

hence

option E) model 4 is correct

when one independent variable is added

then the resultive new model is not always better , it can be better or worse

so

option B) is correct

for example

you see in previous queston r^2 for model 7 is   0.75463873717856 which is less than that of model 4.

Related Questions

Navigate

• Browse (All)
• Browse #
• Subjects

---

---

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