With Rob Kass (Carnegie Mellon University)
People often think of statistics as a collection of particular data-analytic techniques, such as t-tests, chi-squared goodness-of-fit, linear regression, etc., which seem to bear little relation to each other and whose implementation is carried out through a series of somewhat arbitrary rules. But the field of statistics, as an academic discipline, strives for something much deeper, namely, the development and characterization of data collection and analysis methods according to well-defined principles, as a means of quantifying knowledge about underlying phenomena and rationalizing the learning and decision-making process. While many good ideas have helped modernize content and delivery of introductory statistics, I believe more effort should be directed toward giving students an appreciation of the ways the field of statistics makes progress. In other words, I think more can be done to narrow the gap between statistics education and statistical practice.