Data Table Square Feet Price ($000) 395 1,979 3,097 614 1,519 276 967 209 1,877 339 2,595 388 2,554 467 3,243 459 1,447 299 1,176 277 3,229 446 1,137 212 2,012 331 3,145 492 370 Print Done i Data Table www 1,877 339 2,595 388 2,554 467 3,243 459 1,447 299 1,176 277 3,229 446 1,137 212 2,012 331 3,145 492 2,001 376 1,843 372 1,125 238 2,488 492 2,015 394 1,327 275 The accompanying data table contains the listed prices (in thousands of dollars) and the number of square feet for 20 homes listed by a realtor in a certain city. Complete parts a through f below. Click the icon to view the data table. (a) Create a scatterplot for the price of the home on the number of square feet. Does the trend in the average price seem linear? Construct the scatterplot. Choose the correct graph below. A. 3500- 2000- 500- 100 400 700 Price ($000) Does the trend in the average price seem linear? . 3500- C. 700- 2000- 400- 500+ 100+ 100 400 700 500 Price (5000) 2000 3500 Size (Square Feet) D. Q 700- Price ($000) 400- 100- 500 2000 3500 Size (Square Feet) Does the trend in the average price seem linear? A. No, because the scatterplot shows an obvious curved line. B. Yes, because the scatterplot shows an approximate linear pattern. C. Yes, because the scatterplot does not show any obvious pattern. D. No, because the scatterplot does not show any obvious pattern. (b) Estimate the linear equation using least squares. Interpret the fitted intercept and slope. Be sure to include their units. Note if either estimate represents a large e consequently not reliable. Complete the equation for the fitted line below. Estimated Price ($000) = + Size (Square Feet) (Round to three decimal places as needed.) What is the correct interpretation of the intercept? Select the correct choice below and fill in the answer box(es) within your choice. (Round to three decimal places as needed.) OA. The intercept of thousand dollars represents the average cost of the land. B. The intercept is square feet per thousand dollars. For every thousand dollar increase, average size increases by square feet. OC. The intercept of thousand dollars is a large extrapolation and not directly interpretable. OD. The intercept is thousand dollars per square foot. For every one square foot increase, average prices increase by thousand dollars. What is the correct interpretation of the slope? Select the correct choice below and fill in the answer box(es) within your choice. (Round to three decimal places as needed.) OA. The slope is square feet per thousand dollars. For every thousand dollar increase, average size increases by square feet. OB. The slope is C. The slope of thousand dollars per square foot. For every one square foot increase, average prices increase by thousand dollars per square foot is a large extrapolation and not directly interpretable. thousand dollars. OD. The slope of thousand dollars is the cost of a house with 0 square feet. (c) Interpret the summary values r and so associated with the fitted equation. Attach units to these summary statistics as appropriate. 2 = with Se = with (Round to three decimal places as needed.) What is the correct interpretation of the summary values r and s? Select the correct choice below and fill in the answer boxes within your choice. (Round to one decimal place as needed.) OA. The value of r means that the average residual is OB. The value of r means that the equation describes about square feet. The value of s means that the equation does not describe about % of the variation. % of the variation. The value of s means that the average residual is square feet. Se C. The value of r means that the equation describes about % of the variation. The value of s means that the standard deviation of the residuals is thousand dollars. (d) If a homeowner adds an extra room with 555 square feet to her home, can we use this model to estimate the increase in the value of the home? Select the correct choice below and, if necessary, fill in the answer box within your choice. A. Yes. The value of the home increases by thousand dollars. (Round to one decimal place as needed.) B. No, there is no way to estimate the increase in the value of the home. (e) A home with 2,133 square feet lists for $521,000. What is the residual for this case? Is it a good deal? The residual for this case is thousand dollars. A home with this square footage and listing price a good deal because it costs than most houses of this size on average. The residual for this case is thousand dollars. A home with this square footage and listing price (Round to the nearest whole number as needed.) a good deal because it costs than most houses of this size on average. (f) Do the residuals from this regression show patterns? Does it make sense to interpret se as the standard deviation of the errors of the fit? Use the plot of the residuals on the predictor to help decide. A. The residual plot shows no obvious pattern, so it makes sense to interpret se as the standard deviation of the errors. B. The residual plot shows increasing variation, so it does not make sense to interpret s as the standard deviation of the errors because a single value cannot summarize the changing variation. C. The residual plot shows decreasing variation, so it does not make sense to interpret s as the standard deviation of the errors because a single value cannot summarize the changing variation. OD. The residual plot shows an approximate linear pattern, so it makes sense to interpret s as the standard deviation of the errors.