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Assignment part 1
Scenario: You are a consultant who works for the Diligent Consulting Group. Your client, the New Star Grocery Company, believes that there may be a relationship between the number of customers who visit the store during any given month (“customer traffic”) and the total sales for that same month. In other words, the greater the customer traffic, the greater the sales for that month. To test this theory, the client has collected customer traffic data over the past 12-month period, and monthly sales for that same 12-month period (Year 1).
Using the customer traffic data and matching sales for each month of Year 1, create a Linear Regression (LR) equation in Excel, assuming all assumptions for linear regression have been met. Use the Excel template provided (see “Module 2 Case – LR –Year 1” spreadsheet tab), and be sure to include your LR chart (with a trend line) where noted. Also, be sure that you include the LR formula within your chart.
After you have developed the LR equation above, you will use the LR equation to forecast sales for Year 2 (see the second Excel spreadsheet tab labeled “Year 2 Forecast”). You will note that the customer has collected customer traffic data for Year 2. Your role is to complete the sales forecast using the LR equation from Step 1 above.
After you have forecast Year 2 sales, your Professor will provide you with 12 months of actual sales data for Year 2. You will compare the sales forecast with the actual sales for Year 2, noting the monthly and average (total) variances from forecast to actual sales.
To complete the Module 2 Case, write a report for the client that describes the process you used above, and that analyzes the results for Year 2. (What is the difference between forecast vs. actual sales for Year 2—by month and for the year as a whole?) Make a recommendation concerning how the LR equation might be used by New Star Grocery Company to forecast future sales.
Assignment part 2 Written Report
Length requirements:
4–5 pages
(not including Cover and Reference pages) of written discussion and analysis.
· Provide a brief introduction to the problem and background of the problem.
· Your written (in Words) analysis should discuss the logic and rationale used to develop the LR equation and chart.
· Provide complete, meaningful, and accurate recommendation(s) concerning how the New Star Grocery Company might use the LR equation to forecast future sales. (For example, how reliable is the LR equation in predicting future sales?) What other recommendations do you have for the client?
· Avoid redundancy and general statements
>Mod 2 Case – LR – ($ 00)
0
1 January 1
2 February 4
3 March 4 April 421 5 May June 7 July 298 8 August 9 September 10 October November 300 298 12 December 0 0 – 0 – 0 0 ERROR:#DIV/0! Forecast
259 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!Year
1
New Star Grocery Company
Insert chart here
Year 1
Customers
Sales
0
Number
Month
Customers (x)
Sales (y)
XY
X2
Y2
January
1
8
5
2
3
February
2
4
301
March
3
7
3
10
April
421
38
9
May
425
June
259
300
6
July
298
318
August
321
September
215
202
October
282
265
November
235
3
12
11
December
Totals
– 0
Mean
0.00
X-bar
Y-bar
b1
ERROR:#DIV/0!
b0
Y= b0+ b1x
Year 2
New Star Grocery Company
Sales
b1 ERROR:#DIV/0! Year 2
Customers (x)
Actual Y(t)
Forecast F(t)
Variance
b0 ERROR:#DIV/0! January 215 ERROR:#DIV/0! ERROR:#DIV/0!
February
Y= b0+ b1x March
325
April
354
May
258
June
199
July
254
August
299
September
264
October
198
November
223
December
261
Totals
259.08
