Dry Goods Sales The data is for weekly sales in the dry goods department at aWal*Mart store in the Northeast.  Peak values, I.e.spikes, usually occur at holiday periods.  Week 1 is thefirst week of February 2002.  To show continuity, week 1of 2003 is represented as week 54 since week 53 represents the endof fiscal 2002 and start of the 2003 fiscal year. Dollar values areadjusted in order to disguise true sales figures, but trends in thedata are retained for analysis puposes. |
Week | | Sales in $ | |
26 | | 15200 | |
27 | | 15600 | |
28 | | 16400 | |
29 | | 15600 | |
30 | | 14200 | |
31 | | 14400 | |
32 | | 16400 | |
33 | | 15200 | |
34 | | 14400 | |
35 | | 13800 | |
36 | | 15000 | |
37 | | 14100 | |
38 | | 14400 | |
39 | | 14000 | |
40 | | 15600 | |
41 | | 15000 | |
42 | | 14400 | |
43 | | 17800 | |
44 | | 15000 | |
45 | | 15200 | |
46 | | 15800 | |
47 | | 18600 | |
48 | | 15400 | |
49 | | 15500 | |
50 | | 16800 | |
51 | | 18700 | |
52 | | 21400 | |
53 | | 20900 | |
54 | | 18800 | |
55 | | 22400 | |
56 | | 19400 | |
57 | | 20000 | |
58 | | 18100 | |
59 | | 18000 | |
60 | | 19600 | |
61 | | 19000 | |
62 | | 19200 | |
63 | | 18000 | |
64 | | 17600 | |
65 | | 17200 | |
66 | | 19800 | |
67 | | 19600 | |
68 | | 19600 | |
69 | | 20000 | |
70 | | 20800 | |
71 | | 22800 | |
72 | | 23000 | |
73 | | 20800 | |
74 | | 25000 | |
75 | | 30600 | |
76 | | 24000 | |
77 | | 21200 |
1.) Can you identify at least 6 holiday periods or specialevents that cause the spikes in the data?
a.) In each case give the week number, date, and what holiday orspecial event it represents
b.) Which holiday results in the maximum sales for thisdepartment and how much are the sales?
2.) Generate three linear models for this data. Each linearmodel should be generated from a pair of data points.
a.) For each linear model, find the equation of the line. Showyour work. Write the equation in slope intercept form.
b.) For each linear model discuss the meaning of the slope andy-intercept. Also provide an analysis as to why you like or dislikethat particular model
c.) Discuss the rationale behind the model that you believe bestpredicts future results.
3.) Predict and analyze sales for the next four weeks
a.) Using your most preferred linear model, predict sales forthe next four weeks and show calculations
b.) Based on your preferred linear model, compute the percentrate of increase (y2-y1)/y1 for the next four weeks
4.) If you were a manager of this department store, whatrecommendation would you make to the person in charge ofinventory?