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Use the trend projection method, and the trend projection with seasonal adjustment method to create forecasting models in Excel. Next, using the two models, compute the forecasted values of monthly total passengers between 2010 to 2012  Compare the above two models using MAD, MSE, and MAPE  Please explain which of the two models is performing better and why? Use the best model to forecast the monthly total passengers for year 2013

Use the trend projection method, and the trend projection with seasonal adjustment method to create forecasting models in Excel. Next, using the two models, compute the forecasted values of monthly total passengers between 2010 to 2012  Compare the above two models using MAD, MSE, and MAPE  Please explain which of the two models is performing better and why? Use the best model to forecast the monthly total passengers for year 2013

Practical Management Science
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
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  1. Use the trend projection method, and the trend projection with seasonal adjustment method to create forecasting models in Excel. Next, using the two models, compute the forecasted values of monthly total passengers between 2010 to 2012 
  2. Compare the above two models using MAD, MSE, and MAPE  Please explain which of the two models is performing better and why?
  3. Use the best model to forecast the monthly total passengers for year 2013 
Here is a transcription and explanation of the table as it would appear on an educational website: --- **Passenger Data Overview for 2013** This table provides detailed passenger data for the year 2013, organized by month and period number. Please note that the number of passengers for each period is not provided in this table. | **Period #** | **Year** | **Month** | **#Passengers** | |--------------|----------|-----------|-----------------| | 37 | 2013 | Jan | | | 38 | 2013 | Feb | | | 39 | 2013 | Mar | | | 40 | 2013 | Apr | | | 41 | 2013 | May | | | 42 | 2013 | Jun | | | 43 | 2013 | Jul | | | 44 | 2013 | Aug | | | 45 | 2013 | Sept | | | 46 | 2013 | Oct | | | 47 | 2013 | Nov | | | 48 | 2013 | Dec | | **Explanation:** - The table is organized into four columns: Period Number, Year, Month, and Number of Passengers. - Each row corresponds to a period within the year 2013, identified by a sequential period number from 37 to 48. - The months are listed chronologically from January to December. - The "#Passengers" column is currently empty, indicating that the data for the number of passengers is yet to be filled in. This table can be used to input and analyze passenger trends over the course of the year 2013 once the data is available.
Transcribed Image Text:Here is a transcription and explanation of the table as it would appear on an educational website: --- **Passenger Data Overview for 2013** This table provides detailed passenger data for the year 2013, organized by month and period number. Please note that the number of passengers for each period is not provided in this table. | **Period #** | **Year** | **Month** | **#Passengers** | |--------------|----------|-----------|-----------------| | 37 | 2013 | Jan | | | 38 | 2013 | Feb | | | 39 | 2013 | Mar | | | 40 | 2013 | Apr | | | 41 | 2013 | May | | | 42 | 2013 | Jun | | | 43 | 2013 | Jul | | | 44 | 2013 | Aug | | | 45 | 2013 | Sept | | | 46 | 2013 | Oct | | | 47 | 2013 | Nov | | | 48 | 2013 | Dec | | **Explanation:** - The table is organized into four columns: Period Number, Year, Month, and Number of Passengers. - Each row corresponds to a period within the year 2013, identified by a sequential period number from 37 to 48. - The months are listed chronologically from January to December. - The "#Passengers" column is currently empty, indicating that the data for the number of passengers is yet to be filled in. This table can be used to input and analyze passenger trends over the course of the year 2013 once the data is available.
The table presents historical data on passenger numbers across different time periods, allowing for trend analysis and model evaluation based on forecasting efficiency. **Heading Columns:** - **Period #**: Sequential period numbering from 1 to 36. - **Year**: Range from 2010 to 2012. - **Month**: January (Jan) to December (Dec). - **#Passengers**: Passenger counts for each period. - **Trend Projection**: To be filled with projected trends. - **Trend Projection with Seasonal Adjustment**: To be filled with adjusted projections. - **Error Measure**: Evaluation metrics (MAD, MSE, MAPE). **Passenger Data:** - Starts at 151 passengers in January 2010. - Shows fluctuation with a peak of 269 passengers in July and August 2012. - Ends with 224 passengers in December 2012. **Evaluation Criteria:** There’s an additional section for comparing the performance of two models, prompting analysis based on the filled forecasts. The table is designed for recording trend projections and adjustments, followed by calculations of error measures: Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). The final section asks: "Which of the two models performed better and why?" This implies the need to evaluate the forecasting accuracy of filled models using the error metrics once projections are made.
Transcribed Image Text:The table presents historical data on passenger numbers across different time periods, allowing for trend analysis and model evaluation based on forecasting efficiency. **Heading Columns:** - **Period #**: Sequential period numbering from 1 to 36. - **Year**: Range from 2010 to 2012. - **Month**: January (Jan) to December (Dec). - **#Passengers**: Passenger counts for each period. - **Trend Projection**: To be filled with projected trends. - **Trend Projection with Seasonal Adjustment**: To be filled with adjusted projections. - **Error Measure**: Evaluation metrics (MAD, MSE, MAPE). **Passenger Data:** - Starts at 151 passengers in January 2010. - Shows fluctuation with a peak of 269 passengers in July and August 2012. - Ends with 224 passengers in December 2012. **Evaluation Criteria:** There’s an additional section for comparing the performance of two models, prompting analysis based on the filled forecasts. The table is designed for recording trend projections and adjustments, followed by calculations of error measures: Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). The final section asks: "Which of the two models performed better and why?" This implies the need to evaluate the forecasting accuracy of filled models using the error metrics once projections are made.
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