Finding outliers
Outliers represent data points that are so much larger or smaller than the rest of your data points that they cause issues. They can even skew your entire distribution. That one point can throw off all of your results. Here’s an example:
Figure 4.11 – Outlier
In Figure 4.11, we see a scatter chart with the majority of the data points together, but one single point in the upper left-hand corner by itself. Somehow, this observation spent a lot of time in the air but traveled almost no distance. That lone point is probably an outlier. If you were to include that outlier in your calculations, it would artificially pull all of your numbers up and to the right.
In the academic field of statistics, outliers are another controversial issue. There are arguments on how to define what is an outlier and there are arguments about what to do with them. There are specific statistical analyses that only say whether or not a single point...
