"Non-stationary" refers to a condition in which a system's properties change over time. In statistics and data analysis, a non-stationary time series exhibits trends, seasonal patterns, or varying variance, making it difficult to predict future values based on past data. In contrast, a stationary process has constant mean and variance, allowing for more straightforward analysis. Non-stationary behavior is common in fields like economics, climate science, and signal processing, where external factors can influence the data over time, necessitating specialized techniques for accurate interpretation and forecasting.