A regional retailer would like to determine if the variation in average monthly store sales can, in part, be explained by the size of the store measured in square feet. A random sample of stores was selected and the store size and average monthly sales were computed. Complete parts a through c. Use a significance level of where needed. 21 0.10 Click the icon to view the data table between the store size and average monthly sales. 1 a. Compute the simple linear regression model using the sample data to determine whether variation in average monthly sales can be explained by store size. What is the linear regression model based on the sample data? y = + ( )x (Type integers or decimals rounded to two decimal places as needed.) Interpret the slope coefficient. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or decimal rounded to two decimal places as needed.) A. For each additional square foot of store size, the average increase in monthly sales is $ . B. For each additional dollar of monthly sales, the average increase in stores size is square feet. Interpret the intercept coefficient. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or decimal rounded to two decimal places as needed.) A. The size of a store with average monthly sales of $0 is square feet. B. The average monthly sales of a store with 0 square feet is $ . C. A store with no floor space cannot occur; therefore, the y intercept does not have a meaningful interpretation. b. Test the significance of the slope coefficient of the regression model. Use a significance level of . What are the appropriate hypotheses to test? 0.10 A. H0 : 1 0 HA : 1 > 0 B. H0 : 1 < 0 HA : 1 0 C. H0 : 1 > 0 HA : 1 0 D. H0 : 1 0 HA : 1 = 0 E. H0 : 1 0 HA : 1 < 0 F. H0 : 1 = 0 HA : 1 0 Determine the rejection region for the test statistic t. Select the correct choice below and fill in any answer boxes to complete your choice. (Type integers or decimals rounded to three decimal places as needed.) A. t > B. t < or t > C. t < Calculate the simple linear regression test statistic t. t = (Type an integer or decimal rounded to three decimal places as needed.) Since the test statistic (1) in the rejection region, (2) the null hypothesis. Conclude that the regression model (3) significant. This means that knowing x (4) useful help in predicting y. c. Based on the estimated regression model, what percentage of the total variation in average monthly sales can be explained by store size?

1: Data Table of Store Size and Monthly Sales (1) is not is (2) do not reject reject (3) is is not (4) does not provide provides % (Type an integer or decimal rounded to one decimal place as needed.) Store Size (Sq. Ft) Average Monthly Sales 17,380 $581,933.00 15,820 $540,225.00 17,380 $638,615.00 17,200 $574,536.00 15,890 $558,844.00 20,190 $692,706.00 15,350 $554,571.00 16,880 $584,613.00 11,970 $474,063.00 12,430 $523,828.00 15,570 $622,535.00 12,630 $468,485.00 21,510 $735,274.00 14,160 $502,363.00 16,670 $627,924.00 14,850 $600,644.00 18,350 $609,793.00 18,290 $613,622.00 16,590 $694,818.00 19,960 $724,625.00 17,790 $535,924.00