Time series analysis is important in several types of situations; it can be used, for example, to describe changes of a variable in time, predict or forecast through modeling the known variations, and then extrapolate these forward in time or assess how certain external stimuli affects a certain time series variable.
There are three main types of modeling and forecasting methods:
Extrapolation, which is the time series analysis we are focusing on in this chapter. This method simply uses historical data from which a model is built and then used to forecast/predict (that is, extrapolate) into the future.
Judgemental, which is used in, for example, decision making and is common where judgment or beliefs (that is, probabilities) need to be incorporated. This can be the case when no historical time series data exists.
Econometric, which is a regression-based method and usually tries to quantify how and to what extent certain variables/events affect the outcome of the time series....