A regression analysis of 117 homes for sale produced the following model, where

Question

A regression analysis of 117 homes for sale produced the following model, where price is in thousands of dollars and size is in square feet. Price = 47 87 + 0066 (size) a) Explain what the slope of the line says about housing prices and house size. b) What price would you predict for a 2500-square-foot house in this market? c) A real estate agent shows a potential buyer a 1200-foot house, saying that the asking price is exist6000 less than what one would expect to pay for a house of this size. What is the asking price a) Explain what the slope of the line says about housing prices and house size A For every additional square foot of area of a house, the price is predicted to increase by exist66 B. For every exist1 increase in price of a house, the size is predicted to increase by 66 square feet. C. For every exist1000 increase in price of a house, the size is predicted to increase by 0.066 square feet. D. For every additional square foot of area of a house, price is predicted to increase by exist0.066. b) What price would you predict for a 2500-square-foot house in this market? 212.870 c) A real estate agent shows a potential buyer a 1200-square foot house, saying that the asking price is exist6000 less than what one would expect to pay for a house of this size. What is the asking price?

Explanation / Answer

Solution:-

For the first part, substitute 1200 into your regression model:

P(1200) = 47.87 + 0.066(1200)

= 127.07 thousand dollar

or $127,070

The difference in the asking price is $6000 less than one would expect to pay for a home of this size; this difference is known as the residual of the regression.

Therefore, the price is 127,070 - 6,000 = $ 121,070

Related Questions

Navigate

• Browse (All)
• Browse A
• Subjects

---

---

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