Teaching Stats for Data Science

“Data science” is a useful catchword for methods and concepts original to the field of statistics, but typically being applied to large, multivariate, observational records. Such datasets call for techniques not often part of an introduction to statistics: modeling, consideration of covariates, sophisticated visualization, and causal reasoning. This article re-imagines introductory statistics as an introduction to data science and proposes a sequence of 10 blocks that together compose a suitable course for extracting information from contemporary data. Recent extensions to the mosaic packages for R together with tools from the “tidyverse” provide a concise and readable notation for wrangling, visualization, model-building, and model interpretation: the fundamental computational tasks of data science

Fixed-Target CP-Violation Experiments at Fermilab

Studies of CP violation, for 30 years focused primarily on the neutral K meson, are on the threshold of a new era as experiments approach Standard-Model sensitivities in decays of beauty, charm, and hyperons. The array of heavy-quark experiments approved and planned at Fermilab may lead to a significant breakthrough in the next five to ten years.Comment: Revised and expanded for greater clarity and completeness. 15 pages, 6 PostScript figure

Remarks on Muon g−2g-2 Experiments and Possible CP Violation in π→μ→e\pi\to\mu\to e Decay

The first experimental limit on CP violation in pi -> mu -> e decay is extracted from published results of the CERN g-2 experiment.Comment: 2 pages, LaTeX, submitted to Phys. Rev.