| Sumario: | Time series data are chronological sequences of observations produced by regularly and repeatedly measuring some characteristic or characteristics of the same case over time (e.g., aggregate support for the government in a country, the crime rate in a city). Time series analysis is the application of statistical models to time series data. This entry defines time series analysis and distinguishes time series data from other forms of data. It defines important time series notation and terminology. It provides a discussion of the challenges of time series analysis and of key time series fundamentals: autoregression, autocorrelation, serial correlation, stationarity, exogeneity, weak dependence, trending, seasonality, structural breaks, and stability.
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