QNT 275 Week 5 Apply Connect Week 5 Case
You are the manager of a retail store. You want to investigate how metrics can improve the way you manage your business.
Use the Week 5 Data Set to create and calculate the following in Excel®:
Conduct a goodness of fit analysis which assesses orders of a specific item by size (expected) and items you received by size (observed).
Conduct a hypothesis test with the objective of determining if there is a difference between what you ordered and what you received at the .05 level of significance.
Identify the null and alternative hypotheses.
What is your conclusion?
Generate a scatter plot, the correlation coefficient, and the linear equation that evaluates whether a relationship exists between the number of times a customer visited the store in the past 6 months and the total amount of money the customer spent.
Set up a hypothesis test to evaluate the strength of the relationship between the two variables.
Use a level of significance of .05.
Use the regression line formula to forecast how much a customer might spend on merchandise if that customer visited the store 13 times in a 6 month period.
Consider the average monthly sales of 2014, $1310, as your base then
Calculate indices for each month for the next two years (based on the 24 months of data).
Graph a time series plot.
In the Data Analysis Toolpak, use Excel’s Exponential Smoothing option.
Apply a damping factor of .5, to your monthly sales data, then create a new time series graph that compares the original and the revised monthly sales data.
ORDERS VS. SHIPMENTS
Size # Ordered # Received
Extra Small 30 23
Small 50 54
Medium 85 92
Large 95 91
Extra Large 60 63
2X Large 45 42
CUSTOMERS IN PAST 6 MONTHS
Customer # # Visits $ Purchases
1 8 468
2 6 384
3 8 463
4 2 189
5 10 542
6 4 299
7 6 345
8 2 197
9 4 293
10 1 119
11 3 211
12 9 479
13 7 430
14 7 404
15 6 359
16 10 544
17 9 522
18 5 327
19 6 353
20 7 405
21 4 289
22 7 386
23 7 403
24 1 146
25 7 416
26 9 485
27 3 333
28 7 241
29 2 391
30 6 268
MONTHLY SALES ($)
Month $ Sales
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