Often, we observe that two pieces of data, which are not supposed to have any relationship, appear to have a very high correlation. What makes the apparent good correlation is that they both exhibit an upward long-term trend. In addition, fluctuations of the data do not seem to converge around the trend but just seem to move in an upward direction. These types of data statisticians label as “non-stationary.” In contrast, data that converges around a fixed value is labeled “stationary.” Stationary data implies an unchanged structure, something that is stable. Now, if something drifts aimlessly