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.

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 |

(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.

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.