Time Series
This article covers meaning & overview of Time Series from statistical perspective.
What is Time Series?
A time series is a sequence of observation of data points measured over a time interval. The observations are ordered in time as successive observation may be dependent. Time series are plotted via line charts or scatter plots where time, the independent variable on which we have low or no control, is in X axis and the data points are plotted on Y axis.
Time series data can be:-
Discrete- observation spaced at a defined interval. E.g. weekly share price, daily rainfall.
Continuous - observation made at every instance of time. E.g. lie detector, ECG.
Time series are used in pattern recognition, ecometrics, statistics, signal processing, mathematical finance, control engineering, weather forecasting, electroencephalography, earthquake prediction, astronomy, communication engineering or in fields involving temporal measurement.
Time series analysis is a method for analyzing time series data to derive a meaningful statistics and characteristics of data. It helps investor to analyze how an assets, security or other economic variable change with respect to other variables or over time.
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