Data collected at regular time intervals form a time series.
Analysis of time series data should always begin with a time plot.
A random process is a patternless process of independent observations, which vary constantly about their mean over time. Variation from a random process is sometimes to referred to as an irregular component.
Common systematic components found in time series include trend, seasonality, and cyclic (autoregressive) behavior.
The runs test and the autocorrelation function (ACF) are statistical tests of randomness.
A forecast is a prediction of a future value of the time series.