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professor190 [17]
3 years ago
11

A regression analysis of 117 homes for sale produced the following regression equation, where price is in thousands of dollars a

nd size is in square feet. regimage04 (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 1600 square-foot house, saying that the asking price is $4100 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 $145410 and the residual is a positive $4100 . The asking price is $145410 and the residual is a negative $4100 . The asking price is $141310 and the residual is a positive $4100 . The asking price is $141310 and the residual is a negative $4100 .
Business
1 answer:
puteri [66]3 years ago
5 0

Answer:

(a). For every additional square foot of area of a house, the price is predicted to increase by $61

(b) The asking price is $145410 and the residual is a negative $4100

Explanation:

As per the data given in the question,

a) From regression equation Slope = 0.061

So slope = (0.061 × 1,000) ÷ 1 sq. ft.

= $61 per sq. ft.

For every additional square foot area price is increased by $61

b) If size of the house is = 1600 square foot then

Price = 47.81 + 1600*0.061

=$145,410

The asked price is $4,100 less than estimated price and residual is not positive

Hence,

Asking price = $145,410

Residual price = a negative $4,100

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