Data Analytics, Statistical Learning, and Engineering Statistics

Modern Multivariate Statistical Learning

Material collected here comes primarily from a PhD-level Statistics course originally developed to cover the topics of Hastie, Tibshirani, and Friedman’s The Elements of Statistical Learning.  By now much is owed not only to that book, but to Izenman’s Modern Multivariate Statistical Techniques, Principles and Theory for Data Mining and Machine Learning by Clarke, Fokoue, and Zhang, Bishop’s Pattern Recognition and Machine Learning, as well as several other sources.

Available are (or will be):

A set of overview slides from a colloquium talk (given at Los Alamos National Lab, July 16, 2014) entitled “One Statistician’s Perspectives on Statistics and ‘Big Data’ Analytics: Some (Ultimately Unsurprising) Lessons Learned” can be found here: