ties:               Simple moving average, Weighted moving average, Simple Exponential Smoothing, Regression.            • Choose two of the above methods and calculate forecasts for Year 11                  o If you use Weighted moving average, use .5, .3, .2 for the weights (.5 for most recent and so on)                  o If you use Exponential Smoothing, begin with the assumption the Forecast for Year 9 was 1500            ▪ Use .3 for your alpha if you use this method.            • Present your forecast results            • Explain why each of your chosen methods is appropriate for the data and time frame given            • Include MAD, MSE and MAPE

Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
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Problem 1 Forecasting


• All analysis and calculations and report must be done in a single (ONE) Excel file.
• Put your name at the top of the worksheet.
• Make Excel do all of the calculations. (Instructor must be able to see your cell-reference formulas.)
• Include report/answers below the forecasting calculations.
       o Make sure answers are clear, complete and easy to find.
       o Your report must include:
                a. Presentation of forecasts
                b. Explanation of why you chose each of the methods


1. Tom Simpson, Director of the Chamber of Commerce for Exeter township is investigating the past ten years of
tourist visits to the area. The following data has been gathered on number of tourists who signed into the local
information center.


Year     Number of tourists
1          700
2          248
3          633
4          458
5          1410
6          1588
7          1629
8          1301
9          1455
10        1989


Tom is interested in implementing a forecasting system and is investigating the following forecasting methods as
possibilities:
              Simple moving average, Weighted moving average, Simple Exponential Smoothing, Regression.
           • Choose two of the above methods and calculate forecasts for Year 11
                 o If you use Weighted moving average, use .5, .3, .2 for the weights (.5 for most recent and so on)
                 o If you use Exponential Smoothing, begin with the assumption the Forecast for Year 9 was 1500
           ▪ Use .3 for your alpha if you use this method.
           • Present your forecast results
           • Explain why each of your chosen methods is appropriate for the data and time frame given
           • Include MAD, MSE and MAPE

# Forecasting and Error Analysis

## Forecast 1

### Data Table:
| Year | Number of Tourists | Error | | Error\* | | Error\*\* | | Error\*\*\* |
|------|--------------------|-------|------|-------|-------|------|-------|-------|------|
| 1 | 700 | | | | | |
| 2 | 248 | | | | | |
| 3 | 463 | | | | | |
| 4 | 558 | | | | | |
| 5 | 458 | | | | | |
| 6 | 1400 | | | | | |
| 7 | 1588 | | | | | |
| 8 | 1629 | | | | | |
| 9 | 1891 | | | | | |
| 10 | 1488 | | | | | |
| 11 | 1989 | | | | | |
| Total | | | | | | | |
| Average | | | | | | | |

### Errors:
- MAD (Mean Absolute Deviation)
- MSE (Mean Squared Error)
- MAPE (Mean Absolute Percentage Error)

### Explanation:
Explain why forecast 1 is appropriate for the data and time frame given.

## Forecast 2

### Data Table:
| Year | Number of Tourists | Error | | Error\* | | Error\*\* | | Error\*\*\* |
|------|--------------------|-------|------|-------|-------|------|-------|-------|------|
| 1 | 700 | | | | | |
| 2 | 248 | | | | | |
| 3 | 463 | | | | | |
| 4 | 558 | | | | | |
| 5 | 458 | | | | | |
| 6 | 1400 | | | | | |
| 7 | 1588 | | | | | |
| 8 | 1629 | | | | | |
| 9 | 1891 | | | | | |
| 10 | 1488 | | | | | |
| 11 | 1989 | | | | | |
| Total | | | | | | | |
| Average | | | | | | | |

### Errors:
- MAD (Mean Absolute Deviation)
-
Transcribed Image Text:# Forecasting and Error Analysis ## Forecast 1 ### Data Table: | Year | Number of Tourists | Error | | Error\* | | Error\*\* | | Error\*\*\* | |------|--------------------|-------|------|-------|-------|------|-------|-------|------| | 1 | 700 | | | | | | | 2 | 248 | | | | | | | 3 | 463 | | | | | | | 4 | 558 | | | | | | | 5 | 458 | | | | | | | 6 | 1400 | | | | | | | 7 | 1588 | | | | | | | 8 | 1629 | | | | | | | 9 | 1891 | | | | | | | 10 | 1488 | | | | | | | 11 | 1989 | | | | | | | Total | | | | | | | | | Average | | | | | | | | ### Errors: - MAD (Mean Absolute Deviation) - MSE (Mean Squared Error) - MAPE (Mean Absolute Percentage Error) ### Explanation: Explain why forecast 1 is appropriate for the data and time frame given. ## Forecast 2 ### Data Table: | Year | Number of Tourists | Error | | Error\* | | Error\*\* | | Error\*\*\* | |------|--------------------|-------|------|-------|-------|------|-------|-------|------| | 1 | 700 | | | | | | | 2 | 248 | | | | | | | 3 | 463 | | | | | | | 4 | 558 | | | | | | | 5 | 458 | | | | | | | 6 | 1400 | | | | | | | 7 | 1588 | | | | | | | 8 | 1629 | | | | | | | 9 | 1891 | | | | | | | 10 | 1488 | | | | | | | 11 | 1989 | | | | | | | Total | | | | | | | | | Average | | | | | | | | ### Errors: - MAD (Mean Absolute Deviation) -
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