Examples of Non-Stationary Time Series

As you already know, the main difference between non-stationary and stationary data is that the first one has a change in time properties such as the mean, variance, or covariance function.

Examples of non-stationary processes are random walks with or without drift (slow, steady change) and deterministic trends (trends that are constant, positive, or negative, independent of time throughout the life of the series).

An example of a non-stationary time series is recording atmospheric temperature readings measured every 10 seconds. At any given time, the average of the readings equals the true temperature. On the other hand, the average value changes with time - just as the true temperature changes with time.

Also, data on international airline flights is an example of a non-stationary time series. The number of passengers on certain routes varies depending on the season.

Examples of non-stationary data are: