Acknowledgments

To start, I must thank my mother, Gail Lander, for encouraging me to become a math major. Without that I would never have followed the path that led me to statistics and data science. In a similar vein, I have to thank my father, Howard Lander, for paying all those tuition bills. He has been a valuable source of advice and guidance throughout my life and someone I have aspired to emulate in many ways. While they both insist they do not understand what I do, they love that I do it and have helped me all along the way. Staying with family, I should thank my sister and brother-in-law, Aimee and Eric Schechterman, for letting me teach math to Noah, their five-year-old son.

There are many teachers who have helped shape me over the years. The first is Rochelle Lecke, who tutored me in middle school math even when my teacher told me I did not have worthwhile math skills.

Then there is Beth Edmondson, my precalc teacher at Princeton Day School. After I wasted the first half of high school as a mediocre student, she told me I had “some nerve signing up for next year’s AP Calc” given my grades. She agreed to let me take AP Calc if I went from a C to an A+ in her class, never thinking I stood a chance. Three months later, she was in shock as I not only earned the A+, but turned around my entire academic career. She changed my life and without her, I do not know where I would be today. I am forever grateful that she was my teacher.

For the first two years at Muhlenberg College, I was determined to be a business and communications major, but took math classes because they came naturally to me. My professors, Dr. Penny Dunham, Dr. Bill Dunham, and Dr. Linda McGuire, all convinced me to become a math major, a decision that has greatly shaped my life. Dr. Greg Cicconetti gave me my first glimpse of rigorous statistics, my first research opportunity and planted the idea in my head that I should go to grad school for statistics.

While earning my M.A. at Columbia University, I was surrounded by brilliant minds in statistics and programming. Dr. David Madigan opened my eyes to modern machine learning, and Dr. Bodhi Sen got me thinking about statistical programming. I had the privilege to do research with Dr. Andrew Gelman, whose insights have been immeasurably important to me. Dr. Richard Garfield showed me how to use statistics to help people in disaster and war zones when he sent me on my first assignment to Myanmar. His advice and friendship over the years have been dear to me. Dr. Jingchen Liu allowed and encouraged me to write my thesis on New York City pizza, which has brought me an inordinate amount of attention.¹

1. http://slice.seriouseats.com/archives/2010/03/the-moneyball-of-pizza-statistician-uses-statistics-to-find-nyc-best-pizza.html

While at Columbia, I also met my good friend—and one time TA—Dr. Ivor Cribben who filled in so many gaps in my knowledge. Through him, I met Dr. Rachel Schutt, a source of great advice, and who I am now honored to teach alongside at Columbia.

Grad school might never have happened without the encouragement and support of Shanna Lee. She helped maintain my sanity while I was incredibly overcommited to two jobs, classes and Columbia’s hockey team. I am not sure I would have made it through without her.

Steve Czetty gave me my first job in analytics at Sky IT Group and taught me about databases, while letting me experiment with off-the-wall programming. This sparked my interest in statistics and data. Joe DeSiena, Philip du Plessis, and Ed Bobrin at the Bardess Group are some of the finest people I have ever had the pleasure to work with, and I am proud to be working with them to this day. Mike Minelli, Rich Kittler, Mark Barry, David Smith, Joseph Rickert, Dr. Norman Nie, James Peruvankal, Neera Talbert and Dave Rich at Revolution Analytics let me do one of the best jobs I could possibly imagine: explaining to people in business why they should be using R. Kirk Mettler, Richard Schultz, Dr. Bryan Lewis and Jim Winfield at Big Computing encouraged me to have fun, tackling interesting problems in R. Vincent Saulys, John Weir, and Dr. Saar Golde at Goldman Sachs made my time there both enjoyable and educational.

Throughout the course of writing this book, many people helped me with the process. First and foremost is Yin Cheung, who saw all the stress I constantly felt and supported me through many ruined nights and days.

My editor, Debra Williams, knew just how to encourage me and her guiding hand has been invaluable. Paul Dix, the series editor and a good friend, was the person who suggested I write this book, so none of this would have happened without him. Thanks to Caroline Senay and Andrea Fox for being great copy editors. Without them, this book would not be nearly as well put together. Robert Mauriello’s technical review was incredibly useful in honing the book’s presentation.

The folks at RStudio, particularly JJ Allaire and Josh Paulson, make an amazing product, which made the writing process far easier than it would have been otherwise. Yihui Xie, the author of the knitr package, provided numerous feature changes that I needed to write this book. His software, and his speed at implementing my requests, is greatly appreciated.

Numerous people have provided valuable feedback as I produced this book, including Chris Bethel, Dr. Dirk Eddelbuettel, Dr. Ramnath Vaidyanathan, Dr. Eran Bellin, Avi Fisher, Brian Ezra, Paul Puglia, Nicholas Galasinao, Aaron Schumaker, Adam Hogan, Jeffrey Arnold, and John Houston.

Last fall was my first time teaching, and I am thankful to the students from the Fall 2012 Introduction to Data Science class at Columbia University for being the guinea pigs for the material that ultimately ended up in this book.

Thank you to everyone who helped along the way.