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. O (c) Determine the linear correlation coefficient between square footage and asking price. - X Data Table r=] (Round to three decimal places as needed.) O (d) Is there a linear relation between square footage and asking price? Square Footage, x Selling Price ($000s), y 2256 388.2 378.8 O No 3200 1102 185.8 O Yes 1906 327.3 (e) Find the least-squares regression line treating square footage as the explanatory variable. 3103 619.1 y = X +D 2652 351.2 4008 611.2 (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.) 2176 371.5 (f) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice. 2707 440.3 O A. For a house that is 0 square feet, the predicted selling price is thousand dollars. 1636 286.9 (Round to three decimal places as needed.) 1749 265.4 3968 713.8 O B. For a house that is sold for $0, the predicted square footage is. (Round to three decimal places as needed.) O C. For every additional thousand dollars in selling price, the square footage increases by square feet, on average. (Round to three decimal places as needed.) Print Done O D. For every additional square foot, the selling price increases by thousand dollars, on average. (Round to three decimal places as needed.) O E. It is not appropriate to interpret the slope. (g) Is it reasonable to interpret the y-intercept? Why? Select the correct choice below and, if necessary, fill in the answer box to complete your choice. Next