In statistical terms, time series forecasting is the process of analyzing the time series data using statistics and modeling to make predictions and informed strategic decisions. When we associate a temporal or time component to the forecast, it becomes Time Series Forecasting and the data is called as Time Series Data. Hence human decision making is not involved, due to which there is no chance of human bias. In Quantitative Forecasting, data with patterns is available and these patterns can be aptly captured with the help of computers. Since human decision making is involved, there is a chance of bias. There is no data available to study the patterns in order to make forecasting decisions. In Qualitative Forecasting, the forecasting decisions are dependent upon expert opinions. Now, there are two main types of forecasting methods, namely, Qualitative Forecasting and Quantitative Forecasting. Why is forecasting so important? Well, simply because we can make informed decisions. While we listen to, or watch, the NEWS, there is always a separate segment called ‘Weather Report’ where the NEWS commentator provides us with the weather forecast information.
Forecasting is a word we usually associate with the weather.
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