Bibliography - Practical Data Science with R (2014)

Practical Data Science with R (2014)


Adler, Joseph. R in a Nutshell, Second Edition. O’Reilly Media, 2012.

Agresti, Alan. Categorical Data Analysis, Third Edition. Wiley Publications, 2012.

Alley, Michael. The Craft of Scientific Presentations. Springer, 2003.

Brooks, Jr., Frederick P. The Mythical Man-Month: Essays on Software Engineering. Addison-Wesley, 1995.

Casella, George and Roger L. Berger. Statistical Inference. Duxbury, 1990.

Celko, Joe. SQL for Smarties, Fourth Edition. Morgan Kauffman, 2011.

Chakrabarti, Soumen. Mining the Web. Morgan Kauffman, 2003.

Chambers, John M. Software for Data Analysis. Springer, 2008.

Chang, Winston. R Graphics Cookbook. O’Reilly Media, 2013.

Charniak, Eugene. Statistical Language Learning. MIT Press, 1993.

Cleveland, William S. The Elements of Graphing Data. Hobart Press, 1994.

Cover, Thomas M. and Joy A. Thomas. Elements of Information Theory. Wiley, 1991.

Cristianini, Nello and John Shawe-Taylor. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge Press, 2000.

Dalgaard, Peter. Introductory Statistics with R, Second Edition. 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, Third Edition. Cambridge Press, 2006.

Freedman, David. Statistical Models: Theory and Practice. Cambridge Press, 2009.

Freedman, David; Robert Pisani; and Roger Purves. Statistics, Fourth Edition. Norton, 2007.

Gandrud, Christopher. Reproducible Research with R and RStudio. CRC Press, 2014.

Gelman, Andrew; John B. Carlin; Hal S. Stern; David B. Dunson; Aki Vehtari; and Donald B. Rubin. Bayesian Data Analysis, Third Edition. CRC Press, 2013.

Gentle, James E. Elements of Computational Statistics. Springer, 2002.

Good, Philip. Permutation Tests. Springer, 2000.

Hastie, Trevor; Robert Tibshirani; and Jerome Friedman. The Elements of Statistical Learning, Second Edition. Springer, 2009.

James, Gareth; Daniela Witten; Trevor Hastie; and Robert Tibshirani. An Introduction to Statistical Learning. Springer, 2013.

Kabacoff, Robert. R in Action, Second Edition. Manning Publications, 2014.

Kennedy, Peter. A Guide to Econometrics, Fifth Edition. MIT Press, 2003.

Koller, Daphne and Nir Friedman. Probabilistic Graphical Models: Principles and Techniques. MIT Press, 2009.

Kuhn, Max and Kjell Johnson. Applied Predictive Modeling. Springer, 2013.

Loeliger, Jon and Matthew McCullough. Version Control with Git, Second Edition. O’Reilly Media, 2012.

Magee, John. “Operations Research at Arthur D. Little, Inc.: The Early Years.” Operations Research, 2002. 50 (1), pp. 149-153.

Marz, Nathan and James Warren. Big Data. Manning Publications, 2014.

Matloff, Norman. The Art of R Programming: A Tour of Statistical Software Design. No Starch Press, 2011.

Mitchell, Tom M. Machine Learning. McGraw-Hill, 1997.

Provost, Foster and Tom Fawcett. Data Science for Business. O’Reilly Media, 2013.

Sachs, Lothar. Applied Statistics, Second Edition. Springer, 1984.

Seni, Giovanni and John Elder. Ensemble Methods in Data Mining. Morgan & Claypool, 2010.

Shawe-Taylor, John and Nello Cristianini. Kernel Methods for Pattern Analysis. Cambridge Press, 2004.

Shumway, Robert, and David Stoffer. Time Series Analysis and Its Applications, Third Edition. Springer, 2013.

Spector, Phil. Data Manipulation with R. Springer, 2008.

Spiegel, Murray R. and Larry J. Stephens. Schaum’s Outlines Statistics (Fourth Edition). McGraw-Hill, 2011.

Tsay, Ruey S. Analysis of Financial Time Series, 2nd Edition. Wiley, 2005.

Tukey, John W. Exploratory Data Analysis. Pearson, 1977.

Wasserman, Larry. All of Nonparametric Statistics. Springer, 2006.

Wickham, Hadley. ggplot2: Elegant Graphics for Data Analysis (Use R!). Springer, 2009.

Xie, Yihui. Dynamic Documents with R and knitr. CRC Press, 2013.