Auto-correlation describes the dependence between two variables of the same time series at different time periods. Auto-correlation helps determine if there is causal connection between two variables even though there is a time lag between their occurrences. For example, auto-correlation can be useful in sales for determining if a special promotional event occurring at regular intervals is a causal factor in increased sales after the events happen. Auto-correlation answers the question, “Even though X happens before Y, is Y dependent on X?” Not only can auto-correlation be used to determine seasonality, it also helps describe if a series is stationary. A stationary series is one that has properties independent of the time period in which they occurred.

Back to Forecasting Methods