The recent few years have witnessed the widespread application of statistics and machine learning to derive actionable insights and business value out of data in almost all industrial sectors. Hence, it is becoming imperative for business analysts and software professionals to be able to tackle different types of datasets. Often, the data is a time series in the form of a sequence of quantitative observations about a system or process and made at successive points in time. Commonly, the points in time are equally spaced. Examples of time series data include gross domestic product, sales volumes, stock prices, weather attributes when recorded over a time spread of several years, months, days, hours, and so on. The ...
Introduction to Time Series
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