Question

Question 13 (4 points) A cost accountant for Papalote Plastics Inc. is analysing the manufacturing costs of a moulded plastic telephone handset that the company produces. The independent variable is the production lot size (in 1000s of units) and the dependent variable is the total cost of the lot (in $100s). After collecting the data, the accountant generated the following regression analysis summary: SUMMARY OUTPUT Multiple 0 725493625 R Square 0.526341 0.483281091 Adjusted R Square Standard Eror Observatiors 0.898 13 ANOVA AS Significance F Regression Residual 9858759 9.858769 12.22345 0005003502 8.872 006545 12 Coefficients Standard Error t Stot .996 1.161268 3441055 0.005514 Lot Sire (1000 0.358 0.102397 349620s 000500 . From Options #1 to #4, select the correct interpretation of the correlation coefficient. . From options #5 to #8, select the correct interpretation of the slope of the regression line. From options #9 to #12. select the correct interpretation of the coefficient of determination · From options #13 to #16. select the correct interpretation of the standard error of the estimate. 1) There is a strong linear relationship between the cost of the lot and the production lot size. 2) There is a strong. positive linear relationship between the cost of the lot and the production lot size. 3) There is a weak, positive linear relationship between the cost of the lot and the production lot size n the cost of the lot ere is a moderate, negative linear relationship and the production lot size. 5) Each additional $1 in cost will increase the production lot size by 3996. 6) For each additional $100 in cost, the production lot size will increase b 3,996 7) For each additional 1000s units produced, the cost will increase by $35.8d. 8) Each additional unit will cost $0.358 9) 52.63% of the variation in the cost can be explained by the regression equation base on the production lot size 10) 0.5263% of the cost can be explained by the production lot size. 1114832% of the variation in cost can be explained by the production lot size 12) 52.63% of the variation in th e production lot size can be explained by the cost 13) The production lot size differs by 0.898 from the regression line based on the cost of the lot. 14) On average, the cost of the lot differs by $116.13 from the regression line based on the production lot size. 5) The cost differs by $10.24 from the regression line based on the production lot size )On average, the cost of the lot differs by $89.80 from the regression lin based on the production lot size

Answer 1

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