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A moving average is a simple but powerful technique that can be used on time series data or any data recorded in equal intervals, such as time. The history of moving averages goes back at least to 1924, well before computers or hand calculators were in existence. In its simplest form, it is a progressive and repetitive calculation of simple averages and does not require sophisticated computation power. However, using a computer to do the simple calculations and to draw related graphs allows the user to focus on the interpretation of the results. The moving average has uses limited only by the imagination of the user.

It has been used as a technique to smooth data to reveal a trend and as a forecasting technique. It is part of the ARMA methodology for forecasting, where the MA stands for moving average The use in the sophisticated ARMA forecasting process is more of a historical interpretation than an actual implementation.

The theory behind moving averages allows free interpretation and application with few details relating to theory associated with underlying statistical assumptions. It should be viewed as a descriptive statistical technique with many potential theoretical and practical uses. Because it is a very intuitive and practical technique, it is best explained by example.

Moving Average Computation and Use

The software used for illustration purposes is Minitab, a well-known, easy-to-use, and reliable software package that runs on a PC. To start out, consider the following ordered data that were created to illustrate the calculation of a moving average (Figure 1).

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Figure 1 Worksheet

The order refers simply to the fact that the data are in order. If the data are time series, then the order variable would be time at equally spaced intervals.

Because moving averages are often used to smooth data in the sense of eliminating nonmeaningful irregularities in the data, the best practice is to first plot the data to see what they look like. The questions that a plot can answer are, Are there any irregularities in the data that are not meaningful? Do the data display some sort of trend that might be meaningful?

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Figure 2 Time Series Plot of Data

The plot in Figure 2 was produced in Minitab by simply selecting Graph from the main menu and then Time Series Plot. Notice that the data have a slight upward trend with one valley and a couple of peaks.

To explore a moving average, consider a five-term moving average; the number of terms in the moving average is usually determined by trial and error if no other insight is available.

The hand calculations for the first term of the moving average are to simply average the first five data points:

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where MA(1) is the first smoothed value and data(n) is the data column value at Period or Order 1.

The second smoothed value is

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Thus, the calculations continue by shifting down one step and computing the average of the next five terms—thus the term moving average.

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