HighnessFalcon3124
The case note: I have posted this project many times but…
The case
note: I have posted this project many times but always the answers is not clear and not include all the questions, I need excel sheet formulas and clear steps .
the following is links of excel examples:
Time series forecasting (holts model) excel file:
https://myleoonline.tamuc.edu/content/enforced/122144-202320BUSA-511-82B/Tahoe_salt_holts_model.xlsx?_&d2lSessionVal=hn5mhW7pgoB0gBMsRbZ4Iksd6
Time series forecasting (Winters model) excel file:
https://myleoonline.tamuc.edu/content/enforced/122144-202320BUSA-511-82B/Tahoe_salt_winters_model.xlsx?_&d2lSessionVal=hn5mhW7pgoB0gBMsRbZ4Iksd6
*Considering monthly demands for the ABC Corporation as shown below.
Image transcription text
Monthly Demand for ABC Corporation
Question
Forecast the monthly demands for Year 6 using moving average, simple exponential smoothing, Holts’ model, and Winter’s model. In each case, evaluate the bias, TS, MAD, MAPE, and MSE.
Question 1 (6 points): Define a problem statement which reflects the challenge faced in this prediction problem
Question 2 (6 points): Develop a 3-period moving average forecasting model. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts (
Question 3 (6 points): Compute for the model developed in Question 2, compute the error parameters MAD, MSE, MAPE, and TS. Explain these error computations
Question 4 (6 points): Develop a simple exponential smoothing forecasting model, assume, a=0.2. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts
Question 5 (6 points): For the model developed in Question 4, compute the error parameters MAD, MSE, MAPE, and TS.
Question 6 (6 points): For the model developed in Question 4, using Excel Solver optimize the value of a with and objective to minimize MSE. Report your results provide a discussion how optimization improved the forecasting error
Question 7 (6 points): Develop a Holt’s model for forecasting, assume, a=0.3, and b =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts
Question 8 (6 points): For the model developed in Question 7, compute the error parameters MAD, MSE, MAPE, and TS.
Question 9 (6 points): For the model developed in Question 7, using Excel Solver optimize the values of a and b with an objective to minimize MAD. Report your results provide a Discussion how optimization improved the forecasting error
Question 10 (6 points): Develop a Winter’s model for forecasting, assume, a=0.2, b =0.3, and g =0.1. Report the forecasts for year 6 from months January through December inclusive. Discuss briefly these forecasts
Question 11 (6 points): For the model developed in Question 10, compute the error parameters MAD, MSE, MAPE, and TS.
Question 12 (6 points): For the model developed in Question 10, using Excel Solver optimize the values of a, b, and g with an objective to minimize MAPE. Report your results provide a Discussion how optimization improved the forecasting error
Question 13 (6 points): Discuss the model developed in Question 10 is how different from model developed in Question 7,
Question 14 (22 points): Which model you will select and Why and how does the optimization improve the forecasting performance of the methods?
The excel sheet :
https://myleoonline.tamuc.edu/content/enforced/122144-202320BUSA-511-82B/project_data.xlsx?_&d2lSessionVal=hn5mhW7pgoB0gBMsRbZ4Iksd6
