MonthDemandSept.78Oct.80Nov.77Dec.85Jan.Based on the time series data presented above, do the forecasts using 2-month moving average (2-MA) and single exponentialsmoothing (SES) with a = 0.4, and answer the following questions:%3D(i) What is the mean absolute deviation (MAD) for 2-MA?(ii) What is the mean absolute deviation (MAD) for SES a = 0.4 ?(iii) Based on what you got, which method is more accurate?

Answered: Based on the time series data presented…

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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Develop two exponential smoothing forecasts for periods 2 through 11. For the first forecast, use a=0.1. For the second, use a=0.7. Assume that your forecast for period 1 was 205. Click the icon to view the time series data. Find the exponential smoothing forecast for each period when a=0:1 (enter your responses rounded to one decimal place). Period Forecast (0.1) 205 1 2 More Info Period 1 2 3 4 5 6 7 8 9 10 Print Demand 228 249 229 238 231 154 166 157 Demand 228 249 164 161 Done
The accompanying dataset provides data on the monthly usage of natural gas (in millions of cubic feet) for a certain region over two years. Implement the Holt-Winters multiplicative seasonality model with no trend to find the forecast for periods 13-26, where x = 0.5 and y = 0.8. Then find the MAD for periods 13-24. Click the icon to view the monthly use of natural gas data. Use the Holt-Winters multiplicative seasonality model with no trend to find the forecast for periods 13-18, periods 19-24, and then for periods 25 and 26. (Type integers or decimals rounded to two decimal places as needed.) Forecast Period 13 14 15 16 17 18 Natural Gas Usage Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Period Gas Usage 1 2 8699 A WI 3 4 5 7 9 10 11 12 13 14 1516718192021 22 23 24 241 221 155 137 54 34 29 27 30 40 90 201 229 238 242 136 34 34 28 26 27 40 86 187
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Describe why such forecasting devices as moving average , weighted averages and exponential smoothing are not well suited for data series that have trends ?
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