QNT 275 Week 5 Apply Connect Week 5 Case

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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
 
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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