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    Forecasting, Weighted Averages: Various Questions

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    1. With exponential smoothing, does a higher alpha make the forecast MORE or LESS responsive to changes?

    2. With a weighted moving average forecast, to which period is the heaviest weight applied?

    3. Distinguish between the following: seasonal variation, cycles, trends, and random variation.

    4. Distinguish between trend analysis and causal or associative forecasting

    5. How is the accuracy of a forecasting method determined?

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    1. With exponential smoothing, does a higher alpha make the forecast MORE or LESS responsive to changes?
    The smoothing constant, , is assigned a low value if more weight is to be assigned to past data. On the other hand, the smoothing constant, , is assigned a high value if more weight is to be assigned to recent data.
    The higher alpha makes the forecast MORE responsive to sudden changes.
    of 0.5 is very responsive. 1.0 gives 100% of the weight to the prior period, and gives the same results as a prior period calculation. 0.0 eliminates the prior period from the analysis.

    2. With a weighted moving average forecast, to which period is the heaviest weight applied?
    Generally in a weighted moving average forecast, the most recent period is assigned the heaviest weight.

    3. Distinguish between the following: seasonal variation, cycles, trends, and random variation.
    Seasonal variation: Seasonality is a pattern of the demand fluctuation above or below the trend line that is repeated every year.

    Cycle: A movement, up or ...

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