Enter your data for Double Exponential Smoothing (Data tab)

On the Data tab of the Double Exponential Smoothing dialog box, specify the data for the analysis, specify the time scale, and enter the weights for smoothing.

Enter your data

In Y variable, enter a column of numeric data that were collected at regular intervals and recorded in time order. If your data are in multiple columns (for example, you have data for each year in a separate column), you must stack the data into a single column.

In this worksheet, Sales contains the number of computers that are sold each month.

C1
Sales
195000
213330
208005
249000
237040

Time scale labels

(Optional) Enter a column to label the x-axis with values, such as dates. If you don't enter a column, Minitab labels each time period with an integer starting at 1.

Weights to Use in Smoothing

The weights adjust the amount of smoothing by defining how each component reacts to current conditions. Usually, you want to smooth the data enough to reduce the noise (irregular fluctuations) so that the pattern is more apparent. However, don't smooth the data so much that you lose important details.

If you do not know good weights, use the default weights. Then, you can increase or decrease the weight after you examine the time series plot. Lower weights produce a smoother line, and higher weights produce a less smooth line. Use smaller weights for noisy data so that the smoothed values don't fluctuate with the noise.

For level
The level is similar to a moving average of the observations. Usually, a level weight between 0 and 1 works well.
For trend
The trend is similar to a moving average of the differences between consecutive observations. Usually, a trend weight between 0 and 1 works well.

Lower weights give less weight to recent data, so the forecasts (green) follow the overall trend.

Trend = 0.03

Higher weights give more weight to recent data, so the forecasts follow the trend at the end of the data.

Trend = 0.80
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