Moving averages are averages calculated from artificial subgroups of consecutive observations. In control charting, you can create a moving average chart for time-weighted data. In time series analysis, Minitab uses moving average to smooth data and reduce random fluctuations in a time series.
For example, an office products supply company monitors inventory levels each day. They want to use moving averages of length 2 to track inventory levels to smooth the data. They collect data collected for 8 days for one of their products.
The first moving average is 4310, which is the value of the first observation. (In time series analysis, the first number in the moving average series is not calculated; it is a missing value.) The next moving average is the average of the first two observations, (4310 + 4400) / 2 = 4355. The third moving average is the average of observation 2 and 3, (4400 + 4000) / 2 = 4200, and so on. If you want to use a moving average of length 3, three values are averaged instead of two.