Though a time series could be defined more widely, the common simplification is required for analysis is discrete time.
Time series analysis is a specialized method of analyzing a series of data points collected over a period of time. In time series analysis, analysts record data points at consistent intervals over a set period of time, rather than recording data points intermittently or randomly.
What makes time series data different from other data is that analysis can show how a variable changes over time. In other words, time is a key variable that dictates how the data is adjusted over the course of the data points and the final result. It provides an additional source of information and a specified ordering of dependencies between data.
Time series analysis typically requires a large number of data points to ensure consistency and reliability. Using a large data set ensures a representative sample size and allows the analysis to cut out noisy data. Additionally, time series data can be used for forecasting. Predict future data based on historical data.
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