Book Review: The Art of Statistics – How to Learn from Data by David Spiegelhalter

This recent title, “The Art of Statistics – How to Learn from Data,” by University of Cambridge statistician David Spiegalhalter, is an important book on a number of fronts. I particularly appreciated the topics covered in the book that touch on important parts of the Data Science Process: data visualization, linear regression, logarithmic scales, Pierson correlation coefficient, data distributions, logistic regression, ROC curves, classification trees, over-fitting, bootstrap, probability theory, probability distributions, Bayes theory, and much more. I think new data scientists should engage a gentle introduction of these topics before diving into mathematical theory and code.