A production manager wishes to examine the relationship between unit production (number of units produced) and associated costs (total cost). The accompanying table contains data for 10 months of production Complete parts (a) through ) below Click the icon to view the data table. a. Construct a scatter plot for unit production and total cost. Choose the correct graph below. OA OB OC. OD Q Q 70,000 70.000 70.000 70.000 . a . ... 35.000 35 000 3 0- 100 200 Unit Production O 100 200 Uns Production 0-1 0 100 200 Lint Production 0 100 200 Una Prodon b. Fit a quadratic regression model to predict total cost and state the quadratic regression equation + + (Round the x coefficient to four decimal places as needed. Round the X, coefficient to one decimal place as needed. Round the constant to the nearest integer as needed) c. Predict the total cost when production is 87 units The predicted total cost is $1 (Round to two decimal places as needed.) d. Perform a residual analysis on the results and determine whether the regression model is valid Plot the residuals versus 9. Choose the correct graph below. OD Oc . 2 A. Click to select your answer(s). B. C. 70,000 70,000 . Cost (5) 35.000- Production and Costs Data Total Cost ($) 15,189 21,619 30,081 38,504 46,910 55,269 61,707 64,533 65,793 66,358 - Units 20 40 60 80 100 140 160 180 200 120 Print Done mer the regression model is valid. Oc. A production manager wishes to examine the relationship between unit production (number of units produced) and associated costs (total cost). The accompanying table containe data for 10 months of production Complete parta (a) through (k) below. :: Click the icon to view the data table (Round to two decimal places as needed.) d. Perform a residual analysis on the results and determine whether the regression model is valid Plot the residuals versus Y Choose the correct graph below. . . OD . Q 6.000 4.000 2.000 6,000 a 4000- 2.000- 0- -2,000 4.000 -8.000 1 D 80.000 Prediched Y 0 2.000 4000 -6.000 0 80,000 Predicted Y 6.000 4000- 0- -2.000 4000 6.000 80,000 Predicted 5,000 4,000 2.000 0- 2000 -4.000 6,000 0 30,000 Predicted Y Plot the residuals versus X. Choose the correct graph below. OD OC OB a 4,000 2,000 -2.000- 6.000- 4000- 2.000 . 0- -2,000 4,000 -6.000 H 0 *** 220 UN Production e 6.000 6.000 4.000- 2.000 0 -2,000 4.000 -6,000+ 0 220 Unit Production 6.000 4.000- . 2000- 0- -2.000- 4,000 -6000- D 220 Un Production Question View 2 Click to select your answer(s). A production manager wishes to examine the relationship between unit production (number of units produced) and associated costs (total cost). The accompanying table contains data for 10 months of production. Complete parts (a) through ) below. Click the icon to view the data table, . 1 4000- 2.000- 0 -2.000 40003 + 0 Unit Production 0,000 4000- 2.000 0- -2.000 . 4.000 -6000 0 220 Unit Production VT 4.000 2.000 0 -2.000 . 4.000 -6,000 0 220 Un Paduction 4,000 2.000 2.000 4000 -6000 0 220 Une Production Plot the residuals versus X3. Choose the correct graph below OC. OD OA OB 0 8,000 2.000 6,000 4,000-1 2000-2 D -2000-2 4,000 -6,000+ 0 o 40.400 So Unit Prod 6,000 4,000 2.000. 0 -2.000 -4 000 -6.0001 0 40.400 So Unit Prod 6,000 4,000 2,000 0 2.000 4.000 -6.000 40400 SU Prod 2.000 4.000- -8.000- 0 40.400 5 Unit Prod Analyze the residual plots and determine whether the regression model is valid. Choose the correct answer below. O A. There appears to be a linear pattern in the residual plot of unit production squared. Therefore, the model may not be valid OB. There appears to be a curvilinear pattern in the residual plots of total cost, unit production, and unit production squared. Therefore, the model may not be valid C. There appears to be a linear pattern in the residual plots of unit production and unit production squared. Therefore, the model may not be valid D. There does not appear to be any patiems in the residual plots of total cost, unit production, and unit production squared. Therefore, the model is valid 2