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NEED: StatTools & @RISK Your tasks for this Airli...




NEED: StatTools & @RISK Your tasks for this Airline Forecasting case study: You are to create a 3 year forecast, from 2014 through 2016 for both Delta and Southwest airlines that uses the following forecasting and statistical techniques: The one variable summary for both airlines in StatTools ? analyze the results for the two companies, do not just put the output in the report without completely analyzing the results for both airlines. 2. The runs test to determine if the airline data is random or not. 1. The Q-Q plot to determine if the data for both airlines (each done separately) is relatively normal or not. 3. The annual box and whisker plot for both airlines. 4. The moving average with a span of 3 ? in this case it will be 3 years. 5. The simple exponential smoothing forecast. 6. The Holt?s linear method for trends (seasonalized) and the Holt?s linear method deseasonalized. Both methods are required. 7. NOTE: The Winters method for trends and seasonality will not work for annual data, thus it is NOT required for this case study. To decide which of these has the best forecast for both airlines you will concentrate on the following results as provided by the StatTools software: 1. The mean absolute error (MAE) of each forecasting technique; 2. The root mean square error (RMSE) of each forecasting technique; 3. The mean absolute percentage of error (MAPE) of each forecasting technique; 4. The average and cumulative error (see slides 81 to 83 from week 7 PowerPoint) 5. Which forecasting technique best follows the actual earnings line, and provides the best forecasted earnings. NOTE: This technique may be different for the two airlines. 6. NOTE: You MUST include the Airline Forecasting Data ? Table One (page one of the Excel file) completed with the forecast for the years 2014 though 2016 for both airlines. Important things you need to know: 1. You may assume that both companies fiscal year goes from January to December.[1] 2. All operating revenue are in billions of dollars, thus 11.22 = $11,220,000,000 in operating revenue for that year. [1] The company?s actual fiscal year may be different than this assumption, but for this exercise you will use this fiscal year information. Your Tasks: 1. Carry out the various statistical tests as indicated above. 2. Analyze the resulting data, and determine which of the forecasting techniques provides the best forecast for each airline, and why. 3. Report on each of these forecasting techniques in your report, explaining what you did, what you found out, and how you decided which forecast is the best. 4. Put the relevant output graphs, tables and figures INTO the report and discuss them where they are placed in the report. Do NOT just put the output into the Appendix or in the attachment of the report. OUTPUT figures MUST be included and discussed in the report itself. 5. Forecast the next three years of operating revenue for both airlines. 6. Submit your individual report on time as determined by your section?s Monthly/Weekly Calendar. Write a management report (using the required format) suggesting and justifying an appropriate decision regarding the sales forecast. In your report, analyze the patterns of the annual time series; discuss the properties of each forecasting model and their relevance to predicting the series; select the best forecasting models for the series; make your recommendations supported by arguments which are further supported by references to model results and tables or figures in your report. Independent outside research is encouraged to provide relevant background information and/ or to provide more support for your arguments. Please make sure that you use the Assignment Cover Sheet as the first page of your report and the Grading Rubric as the second and third pages of your report (available on BB). Please, embed your Excel spreadsheet showing the appropriate calculations and charts into the Appendix section of your report. How to embed a file into a Word document is explained in Format of a Management Report.


Paper#11523 | Written in 18-Jul-2015

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