The importance of experiment design, good sampling, and probability cannot be overstated, but the twentieth century also brought us huge advancements in statistical testing and our ability to evaluate the quality of estimates, both of which power inferential statistics. Correlation and covariance are other important ideas that were developed in the twentieth century. The computer delivered us from small datasets into “big data.” They learned many different things they could do under the umbrella of “statistics,” and data scientists rely heavily on these new techniques in their day-to-day work, even though they also do a lot of things that fall outside of statistics.