This book is aimed at the data scientist with some familiarity with the R programming language, and with some prior (perhaps spotty or ephemeral) exposure to statistics. Both of us came to the world of data science from the world of statistics, so we have some appreciation of the contribution that statistics can make to the art of data science. At the same time, we are well aware of the limitations of traditional statistics instruction: statistics as a discipline is a century and a half old, and most statistics textbooks and courses are laden with the momentum and inertia of an ocean liner.
Two goals underlie this book:
Tolay out, in digestible, navigable, and easily referenced form, key concepts from statistics that are relevant to data science.
To explain which concepts are important and useful from a data science perspective, which are less so, and why.
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