Excel’s Exponential Smoothing option

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.

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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

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