Prediction of Rainfall for all the States of India Using Auto-Regressive Integrated Moving Average Model and Multiple Linear Regression

India is as an agricultural country where crop productivity contributes to a major share in the economy. For understanding the crop productivity, prediction of rainfall is required and necessary. Forecasting is a challenging work and that too for climate is much more troublesome In this proposed work two methods are used the Box-Jenkins time series ARIMA (Auto Regressive Integrated Moving Average) approach and Multiple Linear Regression (MLR) for prediction of state wise rainfall on monthly scales. The performances of these algorithms will be compared using standard performance metrics, to find out which algorithm gives most accurate results.