One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in a certain region. Complete parts (a) through (h) below.

Square Footage, x

Selling Price ($000s), y

2133

369

3052

355.1

1074

181.5

1968

336.9

3062

614.2

2852

382.3

4292

655.7

2186

373.2

2496

407.4

1718

299.8

1718

260.1

3739

679

a) Which variable is the explanatory variable?

___Square Footage

___Selling Price

(b) Draw a scatter diagram of the data. Choose the correct scatter diagram below.

(c) Determine the linear correlation coefficient between square footage and asking price.

r = ___ (Round to three decimal places as needed.)

(d) Is there a linear relation between square footage and asking price?

___Yes

___No

(e) Find the least-squares regression line treating square footage as the explanatory variable.

ModifyingAbove y with caretyequals=nothingxplus+left parenthesis nothing right parenthesis

(Round to two decimal places as needed.)

(f) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice.

or a house that is 0 square feet, the predicted selling price is nothing thousand dollars.

(Round to two decimal places as needed.)

B. For every additional thousand dollars in selling price, the square footage increases by nothing square feet, on average.

(Round to two decimal places as needed.)

C. For every additional square foot, the selling price

increases by nothing thousand dollars, on average.

(Round to two decimal places as needed.)

D. For a house that is sold for $0, the predicted square footage is

nothing.