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Glossary:Time-series analytics
Time series analysis is a statistical method to analyze the past data within a given duration of time to forecast the future. It comprises of ordered sequence of data at equally spaced interval. Time series data collected over different points in time breach the assumption of the conventional statistical model as correlation exists between the adjacent data points. This characteristic of the time series data breaches is one of the major assumptions that the adjacent data points are independent and identically distributed. This gives rise to the need of a systematic approach to study the time series data which can help us answer the statistical and mathematical questions that come into the picture due to the time correlation that exists.
Time series analysis holds a wide range of applications is it statistics, economics, geography, bioinformatics, neuroscience. The common link between all of them is to come up with a sophisticated technique that can be used to model data over a given period of time where the neighboring information is dependent. In time series, Time is the independent variable and the goal is forecasting.[1]