In exponential smoothing, an alpha of .30 will cause a forecast to react more quickly to a large error than will an alpha of .20.

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Exponential smoothing is a forecasting method that assigns exponentially decreasing weights to past observations. The alpha parameter (also known as the smoothing factor or coefficient) controls how quickly the forecast reacts to new information. A higher alpha value puts more weight on recent data and makes the forecast more sensitive to changes, resulting in a more reactive model. Therefore, an alpha of .30 will cause a forecast to react more quickly to a large error than an alpha of .20.

In Exponential Smoothing, an Alpha of