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 New Star Grocery Company Year 1 Customers Sales ($000) Number Month Customers (x) Sales (y) XY X2 Y2 January 185 230 1 January February 241 301 2 February March 374 310 3 March April 421 389 4 April May 425 421 5 May June 259 300 6 June July 298 318 7 July August 321 298 8 August September 215 202 9 September October 282 265 10 October November 235 312 11 November December 300 298 12 December Totals 0 0 – – – Mean 0 0.00 X-bar Y-bar b1 #DIV/0! b0 #DIV/0! Y= b0+ b1x Provide a brief introduction to/background of the problem. Your written (in Word) 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