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. 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 .

Answer 1

(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

Step-by-step 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