A Sectoral Review of the Impact of Time Series Analysis on Forecasting and Decision-Making

Time Series Analysis(TSA) is one of the statistical tools which are highly relevant to analyse and forecast patterns in which the data is recorded. This kind of analysis can be highly utilized in a wide range of fields including but not limited to finance, health care, transportation, and education. By tracing trends, seasons, and patterns, forecasting of future values based on past observations becomes possible. It is based on these concepts that our paper also deals with key impacts as well as applications in forecasting as well as predicting features of the future based upon Moving averages, Linear Regression, ARIMA, as well as Machine Learning Approaches including Random Forests and Support Vector Machines (SVM) Regression Analysis, Seasonal Decompositions, Deep Learning approaches including LSTM.