Preface

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:

  • To lay 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.

Conventions Used in This Book

The following typographical conventions are used in this book:

Italic

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Constant width

Used for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords.

Constant width bold

Shows commands or other text that should be typed literally by the user.

Tip

This element signifies a tip or suggestion.

Note

This element signifies a general note.

Warning

This element indicates a warning or caution.

Using Code Examples

Supplemental material (code examples, exercises, etc.) is available for download at https://github.com/andrewgbruce/statistics-for-data-scientists.

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Acknowledgments

The authors acknowledge the many people who helped make this book a reality.

Gerhard Pilcher, CEO of the data mining firm Elder Research, saw early drafts of the book and gave us detailed and helpful corrections and comments. Likewise, Anya McGuirk and Wei Xiao, statisticians at SAS, and Jay Hilfiger, fellow O’Reilly author, provided helpful feedback on initial drafts of the book.

At O’Reilly, Shannon Cutt has shepherded us through the publication process with good cheer and the right amount of prodding, while Kristen Brown smoothly took our book through the production phase. Rachel Monaghan and Eliahu Sussman corrected and improved our writing with care and patience, while Ellen Troutman-Zaig prepared the index. We also thank Marie Beaugureau, who initiated our project at O’Reilly, as well as Ben Bengfort, O’Reilly author and statistics.com instructor, who introduced us to O’Reilly.

We, and this book, have also benefited from the many conversations Peter has had over the years with Galit Shmueli, coauthor on other book projects.

Finally, we would like to especially thank Elizabeth Bruce and Deborah Donnell, whose patience and support made this endeavor possible.

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