Economic Order Quantity and Significant Predictor.

1. Stock monetary values over a period of fifty (50) years would well-nigh probably exhibit no cyclic component. a. True b. false 2. On the plot labeled a, which of the under custodytioned is correct? a. thither is a trend present. b. There is a e coherentate relationship. c. There is an obvious outlier. d. There is a negative relationship. 3. On the plot labeled b, thither is an outlier present. a. True b. False 4. On the plot labeled c, which of the following archetypes is more or less appropriate? a. single-parameter exponential smoothing b. regression c. regression with seasonality (classical time-series) . no(prenominal) of the to a higher place are appropriate 5. In a simple linear regression, we are using monthly advertising expenditures (in $000) to hazard monthly dough (in $000). If the to the lowest degree(prenominal) squares equation is y = 21. 5 . 1x and the coefficient of determination is . 49, the correlation coefficient = ______. a. 0. 70 b. -0. 70 c. unable to be act upond from the data. 6. In a simple linear regression, we are using monthly advertising expenditures (in $000) to predict monthly pull ins (in $000). If the least squares equation is y = 21. 5 . x and the coefficient of determination is . 49. The predicted profit = __________ when advertising expenses are $0. a. 21. 5 b. -0. 1 c. $21,500 d. none of the in a higher place. 7. If the correlation coefficient is zero, there is no relationship between x and y. a. True b. False 8. super acid Shoe Stores carries a basic black dress shoe for men that sells at a rate of 500 each quarter. Their current insurance is to bless 500 per quarter, with a fixed hail of $30/order. The yearbook holding cost is 20% of the cost of items held. The following cost complex body part is applicable Order Quantity Price/pair 0-99 $36 100-199 32 200-299 30 three hundred+ 28 For a price of $36, the optimal order quantity is a. 129 b. infeasible for this cost social structure. c. n either of the above. d. both a and b. 9. kelvin Shoe Stores carries a basic black dress shoe for men that sells at a rate of 500 each quarter.Their current form _or_ system of government is to order 500 per quarter, with a fixed cost of $30/order. The yearly holding cost is 20% of the cost of items held. The following cost structure is applicable Order Quantity Price/pair 0-99 $36 100-199 32 200-299 30 300+ 28 The optimal order quantity is a. 129 b. 141 c. 146 d. 300 10. value Inc. arries special holiday items, including Happy Angels (HAs). During the season, the assume for HAs is approximately usually distributed, with a mean of 320 and a standard difference of 30. It costs Foster $5. 00 for each HA unless he orders at least 400, at which the price drops to $4. 50/HA. The HAs retail price is $10. Unsold items leave be given up to a local hospital, with a disposal cost of $0. 05/HA. Mr. Foster estimates that the grace of God cost of each item short is bordering to $0. 25. a. This is a single-period chronicle problem. b. This is an EOQ problem. c. This is a periodic-review problem. d. None of the above 11.Foster Inc. carries special holiday items, including Happy Angels (HAs). During the season, the demand for HAs is approximately normally distributed, with a mean of 320 and a standard deviation of 30. It costs Foster $5. 00 for each HA unless he orders at least 400, at which the price drops to $4. 50/HA. The HAs retail price is $10. Unsold items will be given to a local hospital, with a disposal cost of $0. 05/HA. Mr. Foster estimates that the goodwill cost of each item short is close to $0. 25. A Christmas-tree exercise is appropriate. a. True b. False 12. A regular EOQ model is appropriate when demand is seasonal. a. True . False 13. look into the addicted fixing information I. We are using the hail of radios, TVs, and videodisc players argumentationed with to predict the profit, revenue, and cost for future periods. First, run a model to predict the profit. Select all which apply. a. Radios is a probative predictor. b. TVs is a significant predictor. c. DVDs is a significant predictor. d. The overall model is significant. e. The intercept is positive. f. Severe multicollinearity is present. 14. See the attached Regression Data I. We are using the number of radios, TVs, and DVD players acquited to predict the profit, revenue, and cost for future periods.Next, run a model to predict the cost. Select all which apply. a. Radios is a significant predictor. b. TVs is a significant predictor. c. DVDs is a significant predictor. d. The overall model is significant. e. The intercept is positive. f. Severe multicollinearity is present. 15. See the attached Regression Data I. We are using the number of radios, TVs, and DVD players stocked to predict the profit, revenue, and cost for future periods. Based on the output, which of the following recommendations would be most appropriate? a. We should stock more radios. b.We should stock fewer TVs. c. We should profit floor space, since it is probably constraining our sales ability. d. We should go out the time period. 16. What is the best answer given this information? (3) poser 1 Model 2 Model 3 X-variables 6 4 3 R2 . 9344 . 8857 . 761 Adjusted R2 . 9058 . 8372 . 8497 MSE 5667. 53 6044. 05 5844. 78 a. Model 1 performs the best in all areas. b. Model 2 performs better than Model 3. c. We would most possible prefer Model 1. d. We would most likely prefer Model 2. e. We would most likely prefer Model 3. 17. The table below features three prophecy models used on the same set of data. Select all that apply. Model 1 Model 2 Model 3 Type Single-parameter exponential function 2-parameter Exponential smoothing 3-parameter Exponential smoothing smoothing MSE 8755. 3 4876. 2 5945. 8 a. There is likely a strong seasonal component present. b. There is likely a trend present. c. There is no random component present. d.There is a cyclical component p resent. e. A different smoothing constant could affect the MSE for Model 1. 18. If we increase the order (setup) cost, the order quantity will _____________ if we hold all separate costs constant. a. increase b. decrease c. remain the same as long as there is no shortage cost d. become risky 19. If demand is normally distributed, a. a basic EOQ is appropriate. b. a single-period model could not be appropriate. c. we should produce to fill demand, rather than filling it through orders. d. none of the above would be true. 20. Which of the following methods may be used to determine future order quantities? . forecasting b. regression c. inventory models d. all of the above 21. elevate to the inventory output for Betsys Blue Bonnet bakeshop. Here, Betsy is nerve-wracking to determine the optimal order policy for birthday kits. What is the safety stock? 114____________ 22. adduce to 21. What is Betsys service level if she uses this policy? 87%________________ 23. Refer to 21. If Be tsy changes to a lost sales model, the order quantity would be judge to increase. a. True b. False c. It depends on the cost associated with a lost sale. 24. Refer to the forecasting output for Betsys. This model is appropriate for the type of data. . True b. False 25. Refer to 24. Look at the forecast errors. Which of the following best describes the smear? a. The errors are common mood of what we like to see. b. The errors are randomly distributed. c. The errors are indicative of a problem with the model. d. The errors are indicative of a poor selection of ?. 26. Refer to 24. What recommendation would you make? a. We should use the model as is. b. We should neuter model parameters to improve the fit? c. We should use the model, but use innate caution in doing so. d. We should eliminate some time periods for forecasting. Regression Data I Profit Revenue Radios TVs DVDs Quarter Errors 6318. 96 8395. 1 36 65 4 8 4721. 57 6300. 28 26 48 39 5049. 16 6747. 5 33 51 40 2000 3 32 5249. 44 7028. 6 29 53 45 4 46 5290. 08 7116. 1 32 52 49 2001 1 19 5924. 41 7951. 0 41 58 52 2 23 5251. 97 7031. 09 36 52 44 3 34 4805. 72 6462. 8 31 47 44 4 49 5278. 60 7162. 2 46 49 51 2002 1 22 5301. 77 7136. 5 43 51 46 2 20 6121. 98 8249. 4 45 59 56 3 31 5416. 63 7244. 79 29 55 46 4 51 6552. 89 8718. 1 43 67 48 2003 1 16 6352. 93 8494. 2 46 63 51 2 26 6693. 01 8881. 5 55 68 43 3 37 5761. 97 7669. 0 48 58 39 4 48 5419. 50 7265. 38 33 54 47 2004 -1 22 5474. 64 7302. 7 35 55 44 2 24 4650. 87 6335. 9 41 42 49 4781. 91 6438. 3 48 45 39 MULTI-PERIOD EOQ modelling (Backordering) NORMAL LEAD-TIME DEMAND PROBLEM Betsys Blue Bonnet Bakery disceptation Values Mean of charter scattering mu = 1,000 Stand. Deviation of Demand Distribution sigma = 100 Fixed Cost per Order k = 5,000 one-year Demand Rate A = 52,000 Unit Cost of Procuring an Item c 42. 00 = Annual Holding Cost per Dollar Value h = 0. 20 paucity Cost per Unit pS = 10. 0 optimum Values Optimal Order Quantity Q* = 7,919 Optimal Reorder Point r* = 1,114 expect Demand mu = 1,000 Total Expected Cost TEC(Q*) = $ 67,471. 4 Expected Shortages B(r*) = 6. 47 Probability of Shortage PDr* 0. 13 = Betsys Blue Bonnet Bakery ? = 0. 3 ? = 0. 5 ? = 0. Actual Trend Slope Seasonal calculate Error Quarter t Sales, Yt Tt bt St Ft 2003 W 1 36,500 1988 S 2 43,750 36,500. 00 7,250. 00 1. 20 1988 S 3 59,920 48,601. 00 9,675. 50 1. 23 1988 F 4 87,440 67,025. 55 14,050. 03 1. 0 2004 W 5 102,240 87,424. 90 17,224. 69 1. 17 1988 S 6 123,420 104,144. 98 16,972. 38 1. 19 125,436. 15 (2,016. 15) 1988 S 7 139,610 118,753. 37 15,790. 39 1. 19 149,325. 16 (9,715. 16) 1988 F 8 135,380 125,312. 56 11,174. 79 1. 13 175,522. 72 (40,142. 72) 2005 W 9 129,470 128,753. 89 7,308. 06 1. 04 159,616. 61 (30,146. 1) 1988 S 10 137,57 0 129,989. 43 4,271. 80 1. 08 161,612. 88 (24,042. 88) 1988 S 11 156,630 133,566. 44 3,924. 41 1. 18 159,379. 23 (2,749. 23) 1988 F 12 150,980 136,498. 26 3,428. 11 1. 11 154,702. 82 (3,722. 82) 2006 W 13 143,340 139,362. 57 3,146. 21 1. 03 145,291. 38 (1,951. 38) 1988 S 14 153,360 142,190. 68 2,987. 16 1. 08 154,509. 63 (1,149. 3) 1988 S 15 169,730 144,939. 30 2,867. 89 1. 17 170,664. 76 (934. 76) 1988 F 16 161,990 147,249. 54 2,589. 07 1. 10 164,053. 12 (2,063. 12) 2007 W 17 154,760 149,940. 86 2,640. 19 1. 03 154,408. 75 351. 25 1988 S 18 164,780 152,592. 38 2,645. 85 1. 08 164,739. 26 40. 74 1988 S 19 186,730 156,466. 79 3,260. 13 1. 19 181,930. 65 4,799. 5 1988 F 20 177,880 160,230. 59 3,511. 97 1. 11 176,029. 75 1,850. 25 2008 W 21 170,360 164,152. 06 3,716. 72 1. 04 168,951. 59 1,408. 41 1988 S 22 178,830 167,190. 82 3,377. 74 1. 07 181,270. 26 (2,440. 26) 1988 S 23 195,550 168,732. 72 2,459. 82 1. 16 202,826. 81 (7,276. 81) 1988 F 24 187,220 170,501. 72 2,114. 41 1. 10 189,772. 64 (2,552. 4) 2009 W 25 163,230 168,070. 53 (158. 39) 0. 98 178,936. 82 (15,706. 82) 1988 S 26 162,890 163,137. 87 (2,545. 53) 1. 01 179,944. 64 (17,054. 64) 1988 S 27 174,540 157,361. 67 (4,160. 86) 1. 12 187,085. 45 (12,545. 45) 1988 F 28 163,130 151,724. 53 (4,899. 00) 1. 08 168,543. 79 (5,413. 79) 2010 W 29 144,517. 6 1988 S 30 143,788. 09 1988 S 31 153,515. 48 1988 F 32 142,720. 95 MSE = 175,943,211