FORECASTING DATA

Forecasting Data

 

You work as a consultant for the Excellent Consulting Group in this order description scenario. Your client desires the ability to predict sales on a monthly basis and is convinced that there is a reliable correlation between sales and the volume of visitors to their website in the preceding month. The client has gathered information on website visits, sales of one of its goods, sales of a lottery app for smartphones, and other metrics to test this notion.
Case Assignment
Analyze the data using Excel and linear regression to decide how to forecast based on website hits.
Then, using the monthly hit data, forecast the subsequent three months. Determine the forecasting error by comparing the forecast to the actual sales. Information on actual sales (Jan. 402, Feb. 380, Mar. 379, and Apr. 405)
Then, in a report to your manager and the client, briefly outline the outcomes you got. Make a suggestion on how this could be applied to forecasting.
There should be two files on paper: an Excel file and a Word document, respectively.
Data: Included the data in the Word document Case 3 Data.docx. Use Excel to conduct your analysis using this data.
Assignment Evaluation of Expectations
• Excel’s accurate and comprehensive linear regression analysis
Report in writing: (Paragraphs should have headings.)
• Minimum length requirements are four pages (excluding the cover and reference pages).
• Give a succinct history or introduction to the issue.
• A thorough and precise Excel analysis
• Written analysis that explains in detail the underlying assumptions, justifications, and logic utilized to support the Excel analysis.
• Detailed, pertinent, and exact recommendations

Note: Refer to the attachments for Case 3: Assignment Data and detailed instructions. Two files should be included with the paper: a Word document and an Excel file.
3 Case Data
The statistics for website visits and app sales (the number of lottery apps) are shown below.
Sales Up Month
January 1200,420, February 820,545, March 1151,301, April 1050,510
May 1180 485
Jun 1047 525
Jul 1102 460
Aug 1054 500
Oct. 1071, November 1120, December 1287, and January 1164
February 1159, March 1298, April
Important: Because the idea holds that hits anticipate sales for the next month (for example, the 1,200 hits in January are associated with February’s sales of 545), be sure to move the monthly sales up by one month. As a result, your data will appear as follows:
Sales Up Month
Feb. 820, 301; Jan. 1200, 545
Apr 1050 485 Mar 1151 510
June 1047, 460; May 1180, 525
Aug 1054 402 Sep 1254 584 Oct 1071 422 Nov 1120 514 Dec 1287 441 Jul 1102 500

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To forecast sales for February through April, use the monthly hits from January through March.
Once you’ve done so, request from your instructor the information on actual sales for Jan. 1 through Apr.

Unit 3 Case
Using decision trees and linear regression forecasting
Assignment Summary
Scenario: For the Excellent Consulting Group, you serve as a consultant. Your client desires the ability to predict sales on a monthly basis and is convinced that there is a reliable correlation between sales and the volume of visitors to their website in the preceding month. The client has gathered information on website visits, sales of one of its goods, sales of a lottery app for smartphones, and other metrics to test this notion.
Assignment: Case
Analyze the data using Excel and linear regression to decide how to forecast based on website hits.
Then, using the monthly hit data, forecast the subsequent three months. Determine the forecasting error by comparing the forecast to the actual sales. Information on actual sales (Jan. 402, Feb. 380, Mar. 379, and Apr. 405)
Then, in a report to your manager and the client, briefly outline the outcomes you got. Make a suggestion on how this could be applied to forecasting.
Download the data in the Word document Case 3 Data.docx. Use Excel to conduct your analysis using this data.
Analysis of Assignment Expectations
• Excel’s accurate and comprehensive linear regression analysis
Report in writing: Paragraph headings should be used.
• Minimum length requirements are four pages (excluding the cover and reference pages).
• Give a succinct history or introduction to the issue.
• A thorough and precise Excel analysis
• Written analysis that explains in detail the underlying assumptions, justifications, and logic utilized to support the Excel analysis.
• Detailed, pertinent, and exact recommendations

 

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