# Week 5 (and final assignment)

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 and items you received by size.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.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 to:Calculate indices for each month for the next two years. 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. Create a new time series graph that compares the original and the revised monthly sales data.
week5dataset.xlsx

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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
1
8
2
6
3
8
4
2
5
10
6
4
7
6
8
2
9
4
10
1
11
3
12
9
13
7
14
7
15
6
16
10
17
9
18
5
19
6
20
7
21
4
22
7
23
7
24
1
25
7
26
9
27
3
28
7
29
2
30
6
CUSTOMERS IN PAST 6 MONTHS
\$ Purchases
468
384
463
189
542
299
345
197
293
119
211
479
430
404
359
544
522
327
353
405
289
386
403
146
416
485
333
241
391
268
MONTHLY SALES (\$)
Month
\$ Sales
Jan
1375
Feb
1319
Mar
1222
Apr
1328
May
1493
Jun
1492
Jul
1489
Aug
1354
Sep
1530
Oct
1483
Nov
1450
Dec
1495
Jan
1545
Feb
1454
Mar
1322
Apr
1492
May
1678
Jun
1645
Jul
1580
Aug
1493
Sep
1719
Oct
1573
Nov
1629
Dec
1680

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