Data & Analytics
(Stationarität)Stationarity
Also known as:
Stationary Process
Weak Stationarity
Covariance Stationarity
Updated: 2/11/2026
A time series is stationary when its statistical properties remain constant over time.
Quick Summary
Stationarity means constant statistical properties over time – fundamental prerequisite for ARIMA and others.
Explanation
Most classical models require stationary data. ADF test and KPSS test check stationarity.
Marketing Relevance
Most important prerequisite for classical time series modeling. Violation leads to spurious regression.
Common Pitfalls
Judging only visually. Over-differencing. Confusing trend-stationary vs. difference-stationary.
Origin & History
From stochastic process theory (1930s). ADF test (Dickey & Fuller, 1979). KPSS test (1992).
Comparisons & Differences
Stationarity vs. Trend
Stationary series have no trend; trend-containing series must be differenced.