Complete the following steps to specify the column of data that you want to analyze.
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.
(Optional) In Time scale labels, 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.
In MA length, enter the number of consecutive observations that Minitab uses to calculate the moving averages. For example, for monthly data, a value of 3 indicates that the moving average for March is the average of the observations from March, February, and January. If there is a seasonal pattern, you can set the length equal to the length of the seasonal pattern.
The moving average length adjusts the amount of smoothing. Typically, 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. Lower values produce a less smooth line. Higher values produce a smoother line. To calculate naive forecasts, use a moving average length of 1. For more information on naive forecasting, go to Forecasting with time series analysis and click "What is naive forecasting?".
In this worksheet, Sales contains the number of computers that are sold each month.
Center the moving averages
Select to plot each moving average value at the center of its range, instead of at the end.
If you plot the fitted values, Minitab starts them one position ahead of the moving average values.