Linear Regression and Simple Exponential Smoothing (SES) Forecasting, assignment help

Description

Module 2 – Case
Linear Regression and Simple Exponential Smoothing (SES) Forecasting
Assignment Overview
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).
Case Assignment
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.
Data: Download the Module 2 Case template here: Data chart for BUS520 Case 2. Use this template to complete your Excel analysis.
Assignment Expectations
Excel Analysis
Conduct accurate and complete Linear Regression analysis in Excel.
Use Excel support to find information on linear regression in Excel: https://support.office.com/en-us/Search/results?query=linear regression
Written Report

Length requirements: 4–5 pages minimum (not including Cover and Reference pages). NOTE: You must submit 4–5 pages of written discussion and analysis. This means that you should avoid use of tables and charts as “space fillers.”
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 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?
Write clearly, simply, and logically. Use double-spaced, black Verdana or Times Roman font in 12 pt. type size.
Have an introduction at the beginning to introduce the topics and use keywords as headings to organize the report.
Avoid redundancy and general statements such as “All organizations exist to make a profit.” Make every sentence count.
Paraphrase the facts using your own words and ideas, employing
quotes sparingly. Quotes, if absolutely necessary, should rarely exceed
five words.
Upload both your written report and Excel file to the case 2 Dropbox.

Here are some guidelines on how to build critical thinking skills.

Emerald Group Publishing. (n.d.). Developing Critical Thinking. Retrieved from http://www.emeraldinsight.com/learning/study_skill…

Tags:
Linear Regression

Simple Exponential Smoothing (SES) Forecasting

User generated content is uploaded by users for the purposes of learning and should be used following Studypool’s honor code