Question: MATH 1220 Fall '16 Management Calculus Project #1 Wal*Mart Dry Goods Sales 2002-2003 All projects must be printed on letter size paper. No electronic copies
MATH 1220 Fall '16 Management Calculus Project #1 Wal*Mart Dry Goods Sales 2002-2003 All projects must be printed on letter size paper. No electronic copies or handwritten ones will be accepted. All content must be printed - no handwritten mathematics, graphs, labels, etc. All projects must be stapled. Students must work individually, no partners or teams. Violation of this policy will result in a grade of zero for the project, in addition to any other punishment under the university academic honesty code. Note that, in addition to answering the project questions, students will also be graded on presentation and writing. Generate supporting Excel spreadsheet(s) and graphs (use scatter plots) to answer the following questions for the Dry Goods 2002-2003 data: 1. Modeling the data linearly a. Generate a linear model for this data by using the two points at weeks 34 and 72. (5 pts.) b. What are the marginal sales for this department using this model? (5 pts.) c. Generate a least squares linear regression model for this data. (5 pts.) d. How good is this regression model? (5 pts.) e. What are the marginal sales for this department using this regression model? (5 pts.) f. Compare the two models. Which do you feel is better? Explain your rationale. (5 pts.) 2. Modeling the data quadratically a. Generate a quadratic regression model for this data. (5 pts.) b. What are the marginal sales for this department using this model? (5 pts.) c. Calculate the model generated relative extremum value. Show backup analytical work. (5 pts.) d. Compare the actual and model generated relative extremum values. (5 pts.) 3. Analyzing and Comparing models a. Which model do you feel best predicts future trends? Explain your rationale. (10 pts.) b. Based on the model selected, what type of seasonal adjustments, if any, would be required to meet customer needs? (10 pts.) c. What do you think causes the spikes in the data? If we removed these outliers, how would that affect the models generated? (10 pts.) Presentation - 15 pts. Writing - 5 pts. Wal*Mart Dry Goods Sales 2002-2003 The data is for weekly sales in the dry goods department at the Methuen Wal*Mart store in fiscal 2002-2003. Week 1 is the first week of February 2002. To show continuity, week 1 of 2003 is represented as week 54 since week 53 represents the end of fiscal 2002 and start of the 2003 fiscal year. Dollar values are adjusted in order to disguise true sales figures, but trends in the data are retained for analysis purposes. Week 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 Sales in $ 15200 15600 16400 15600 14200 14400 16400 15200 14400 13800 15000 14100 14400 14000 15600 15000 14400 17800 15000 15200 15800 18600 15400 15500 16800 18700 21400 20900 18800 22400 19400 20000 18100 18000 19600 19000 19200 18000 17600 17200 19800 19600 19600 20000 20800 22800 23000 20800 25000 30600 24000 21200
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