Jx 4 B C 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Cost 54.4 52.1 60.2 53.8 51.7 57.1 61.1 49.8 53.9 48.2 47.5 57.4 59.6 58.2 58.7 58.1 48.4 63.4 62.5 62.5 62.7 61.2 55.9 51.3 57.1 58.2 55.8 54.9 54.7 50.2 60.8 54.8 51.3 51.9 49.8 55.5 Quantity 844 503 300 869 525 1030 288 577 490 588 606 325 1160 1072 308 1140 627 214 207 1174 1190 1166 1067 655 384 367 927 890 495 780 1168 403 741 712 612 870 27 28 29 30 31 32 33 34 35 36 37 38 b. Estimate the linear regression model to predict inventory cost as a function of order quantity. Then estimate the quadratic regression model to predict inventory cost as a function of order quantity and order quantity squared. (Enter all values rounded to 4 decimal places.) Cosi Cost- Quantity: Quantity Quantity 1. Evaluate the linear model in terms of variable significance (a=0.05) and adjusted ? The adjustedis rcfck to select and the explanatory variable Chek to select significant. c-2. Evaluate the quadratic model in terms of variable significance la = 0.05) and adjusted (Round your answer to 2 decimal places.) The adjusted 18 and the explanatory variables Gelet significant d. Use the best fitting model to predict manthly inventory cost for an order quantity of B00 units. (Do not round the estimates or Intermediate calculations. Round your final answer to 3 decimal places.) model a test providing a predicted value of The co The inventory manager at a warehouse distributor wants to predict inventory cost Cost in $) based on order quantity (Quantity in units). She thinks it may be a nonlinear relationship since its two primary components move in opposite directions: (1) order processing cast costs of procurement personnel, shipping. transportation, which decreases as order quantity increases (due to fewer orders needed), and (2) holding cost costs of capital facility, warehouse personnel, equipment, which increases as order quantity increases (due to more inventory held). She has collected monthly Inventory costs and order quantities for the past 36 months. A portion of the data is shown in the accompanying table. Jx 4 B C 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Cost 54.4 52.1 60.2 53.8 51.7 57.1 61.1 49.8 53.9 48.2 47.5 57.4 59.6 58.2 58.7 58.1 48.4 63.4 62.5 62.5 62.7 61.2 55.9 51.3 57.1 58.2 55.8 54.9 54.7 50.2 60.8 54.8 51.3 51.9 49.8 55.5 Quantity 844 503 300 869 525 1030 288 577 490 588 606 325 1160 1072 308 1140 627 214 207 1174 1190 1166 1067 655 384 367 927 890 495 780 1168 403 741 712 612 870 27 28 29 30 31 32 33 34 35 36 37 38 b. Estimate the linear regression model to predict inventory cost as a function of order quantity. Then estimate the quadratic regression model to predict inventory cost as a function of order quantity and order quantity squared. (Enter all values rounded to 4 decimal places.) Cosi Cost- Quantity: Quantity Quantity 1. Evaluate the linear model in terms of variable significance (a=0.05) and adjusted ? The adjustedis rcfck to select and the explanatory variable Chek to select significant. c-2. Evaluate the quadratic model in terms of variable significance la = 0.05) and adjusted (Round your answer to 2 decimal places.) The adjusted 18 and the explanatory variables Gelet significant d. Use the best fitting model to predict manthly inventory cost for an order quantity of B00 units. (Do not round the estimates or Intermediate calculations. Round your final answer to 3 decimal places.) model a test providing a predicted value of The co The inventory manager at a warehouse distributor wants to predict inventory cost Cost in $) based on order quantity (Quantity in units). She thinks it may be a nonlinear relationship since its two primary components move in opposite directions: (1) order processing cast costs of procurement personnel, shipping. transportation, which decreases as order quantity increases (due to fewer orders needed), and (2) holding cost costs of capital facility, warehouse personnel, equipment, which increases as order quantity increases (due to more inventory held). She has collected monthly Inventory costs and order quantities for the past 36 months. A portion of the data is shown in the accompanying table