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# Forecast Tools

## Exponential Smoothing Tool

Figure 20. Exponential Smoothing Tool Dialog

The Exponential Smoothing tool performs the exponential smoothing for the given set or sets of values. Each value in the smoothed set is predicted based on the forecast for the prior period. The formula to calculate the forecast is: `F(t+1) = F(t) + (1 - `dampingFactor`) * (A(t) - F(t))`, where `A(t)` is the `t`th value in the original data set.

Specify the cells containing the datasets in the "`Input Range`" entry. The entered range or ranges are grouped into datasets either by rows or by columns.

If you have labels in the first cell of each data set, select the "`Labels`" option.

Specify prior forecast adjustment value in the "`Damping factor`" entry. A value, for example, between 0.2 and 0.3 represents 20 to 30 percent error adjustment in the prior forecast.

Figure 21. Some Example Data for the Exponential Smoothing Tool

Example 6. Using the Exponential Smoothing Tool

Figure 21 shows some example data and Figure 22 the corresponding output.

Figure 22. Exponential Smoothing Tool Output

## Moving Average Tool

Figure 23. Moving Average Tool Dialog

Use the moving average tool to calculate moving averages of one or more data sets. A moving average provides useful trend information of the data that is lost in a simple average. In addition, moving averages can be used to eliminate random variance. For example, use this tool to create a smoother curve of a stock prize.

Specify the cells containing the datasets in the "`Input Range`" entry. The entered range or ranges are grouped into datasets either by rows or by columns.

If you have labels in the first cell of each data set, select the "`Labels`" option.

Specify the "`Interval`" for the moving average. The interval `i` is the number of consecutive values to be included in each moving average.

The results are given in one column for each dataset Each row represents the moving average of the corresponding row or column in the input range. The moving average cannot be calculated for the first `k` rows in the input range where `k` is smaller than the given interval `i`.

Figure 24. Some Example Data for the Moving Average Tool

Example 7. Using the Moving Average Tool

Figure 24 shows some example data and Figure 25 the corresponding output.

Figure 25. Moving Averages Tool Output

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