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• Cristianini, Nello, and John Shawe-Taylor. An Introduction to Support Vector Machines. Cambridge Press, 2000.
• Dalgaard, Peter. Introductory Statistics with R, 2nd ed. Springer, 2008.
• Dimiduk, Nick, and Amandeep Khurana. HBase in Action. Manning Publications, 2013.
• Efron, Bradley, and Robert Tibshirani. An Introduction to the Bootstrap. Chapman and Hall, 1993.
• Everitt, B. S. The Cambridge Dictionary of Statistics, 2nd ed. Cambridge Press, 2006.
• Freedman, David. Statistical Models: Theory and Practice. Cambridge Press, 2009.
• Freedman, David, Robert Pisani, and Roger Purves. Statistics, 4th ed. Norton, 2007.
• Gandrud, Christopher. Reproducible Research with R and RStudio, 2nd ed. CRC Press, 2015.
• Gelman, Andrew, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. Bayesian Data Analysis, 3rd ed. CRC Press, 2013.
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• Krzanowski, W. J., and F. H. C. Marriott. Multivariate Analysis, Part 1, Edward Arnold, 1994.
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• Spector, Phil. Data Manipulation with R. Springer, 2008.
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• Tukey, John W. Exploratory Data Analysis. Pearson, 1977.
• Vapnik, Vladimir N. Statistical Learning Theory, Wiley-Interscience, 1998.
• ———The Nature of Statistical Learning Theory, 2nd ed. Springer, 2000.
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• ———All of Statistics. Springer, 2004.
• Wickham, Hadley. Advanced R. CRC, 2014.
• ———ggplot2: Elegant Graphics for Data Analysis (Use R!). Springer, 2009.
• ———R Packages: Organize, Test, Document, and Share Your Code. O’Reilly Media, 2015.
• Wilkinson, Leland. The Grammar of Graphics, 2nd ed. Springer, 2005.
• Xie, Yihui. Dynamic Documents with R and knitr. CRC Press, 2013.
• Zumel, Nina, and John Mount. “vtreat: a data.frame Processor for Predictive Modeling.” 2016. https://arxiv.org/abs/1611.09477.