What are two key concepts in time series analysis?

Most commonly, a time series is a sequence taken at successive equally spaced points in time . Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average.

In this chapter, you will be introduced to some of the fundamental concepts of time series data and time series analysis: autoregression, autocorrelation, serial correlation, stationarity, exogeneity, weak dependence, trending, seasonality, structural breaks, and stability .

Time series analysis is a specific way of analyzing a sequence of data points collected over an interval of time . In time series analysis, analysts record data points at consistent intervals over a set period of time rather than just recording the data points intermittently or randomly.