A regression analysis of 117 homes for sale produced the following regression eq
ID: 3155958 • Letter: A
Question
A regression analysis of 117 homes for sale produced the following regression equation, where price is in thousands of dollars and size is in square feet.
(a) What does the slope of the line say about housing prices and size?
For every $1,000 increase in price of a house, the size is predicted to increase by 0.061 square foot.
For every additional square foot of area of a house, the price is predicted to increase by $61.
For every additional square foot of area of a house, the price is predicted to increase by $0.061.
For every $1 increase in price of a house, the size is predicted to increase by 61 square feet.
(b) A realtor shows a potential buyer a 1000 square-foot house, saying that the asking price is $5,000 less than what one would expect to pay for a house of this size. What is the asking price of this house and what is the residual?
The asking price is $108,810 and the residual is a positive $5,000.
The asking price is $108,810 and the residual is a negative $5,000.
The asking price is $103,810 and the residual is a positive $5,000.
The asking price is $103,810 and the residual is a negative $5,000.
Explanation / Answer
(a) What does the slope of the line say about housing prices and size?
By definition of slope, and as price is in thousands, 0.061*1000 = 61,
b: For every additional square foot of area of a house, the price is predicted to increase by $61. [ANSWER, B]
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b)
As
Price = 47.81+ 0.061*size
as size = 1000, then
Price = 47.81+ 0.061*1000 = 108.81
Hence, Price = 108.81*1000 = 108 810.
Also, as " the asking price is $5,000 less than what one would expect to pay for a house of this size", then residual = -5000, so
OPTION B: The asking price is $108,810 and the residual is a negative $5,000. [ANSWER, B]
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