Introduction to Data Science
Using the R Language for Statistical Computing and Graphics
Jeffrey M. Stanton
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Introduction to Data Science, by Jeffrey Stanton, provides non-technical readers with a gentle introduction to essential concepts and activities of data science. For more technical readers, the book provides explanations and code for a range of interesting applications using the open source R language for statistical computing and graphics. The book is suitable for an introductory course in data science where students have a varied background or as a supplement to an advanced analytics course where students would benefit from an introduction to R. This book is distributed under a Creative Commons license that permits adaptation and redistribution for non-commercial purposes.
What's New in Version 3.0
Version 3.0 of this book contains a new chapter on data mining with support vector machines. Instructions for using Twitter's OAuth functions have been enhanced with additional information for Windows users.
An Important, Accessible Work
This book hit my desk at just the right moment. I am currently working on a project which considers the varied ways a company is targeting its promotional activities and reviewing Google Analytics for past activities. I find this work fascinating. Professor Stanton is a master at making the complex accessible. I took his introductory statistics course and not only learned but actually enjoyed every minute of the course. After reading the first chapter of this new book, I'm already hooked. This is an important text for anyone who wants to understand how data underpins decision-making and impacts our world.