Regularity is finding patterns in the randomness of an event or events. Both, regularity and randomness are important in statistics because statistics is applying the data from random events into charts or graphs that show patterns so that the data can be analyzed and applied to a larger or entirely different problem or question. Regularity is necessary to interpret the results to that they can be used to predict events in the future. It was clear that all men would not be needed for the war and that those assigned high numbers would probably never be called to serve. In contrast, those with low numbers most certainly would be drafted.
Statisticians rely on looking at both to determine the significance of a certain outcome.
Regularity is important because it is patterns that provide an order in randomness that unanalyzed can seem like chaos. Randomness and regularity are important to the study of statistics because everything that statistics takes into consideration contains these two elements in some way. Randomness is a part of statistics that is present each time data is collected. Every time the same data is collected, from different samplings, a different percentage of a certain aspect of the data will result. Regularity is also important to statistics because without it, statisticians would never know if changes were resulting.