Time series analysis is an econometric technique economists, researchers, and other analysts use to model and subsequently forecast data, or moreover, other times series, where times are discrete (t=1,2,3…n) or continuous (t>0). It is most useful on large data sets, and consists of three primary components, including seasonality, trend, and random irregularity—or noise. Hence, both univariate and multivariate time series analysis can be used in a host of disciplines, not just economics…