Autocorrelation analysis is a statistical technique used to examine dependencies in a data set. It measures the similarity of a variable to itself at different points in time. It can be used to examine the stationary and trend properties of a series and determine if it is self-correlated. Autocorrelation analysis is often used to predict future values of a behavior or event.