Bibliography: Data Science
James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013), An Introduction to Statistical Learning, New York, NY: Springer Science+Business Media, LLC.
Kuhn, M., and Johnson, K. (2013), Applied Predictive Modeling, New York , NY: Springer Science+Business Media, LLC.
Milliken, G. A., and Johnson, D. E. (1989), Analysis of Messy Data, Volume 2: Nonreplicated Experiments, Boca Raton, FL: Taylor & Francis Group.
Milliken, G. A., and Johnson, D. E. (2002), Analysis of Messy Data, Volume III: Analysis of Covariance, Boca Raton, FL: CRC Press LLC.
Milliken, G. A., and Johnson, D. E. (2009), Analysis of Messy Data, Volume 1: Designed Experiments (2nd ed.), Boca Raton, FL: Taylor & Francis Group, LLC.
Sinha, P. P. (2014), Bioinformatics with R Cookbook, Birmingham, UK: Packt Publishing Ltd.
Kuhn, M., and Johnson, K. (2013), Applied Predictive Modeling, New York , NY: Springer Science+Business Media, LLC.
Milliken, G. A., and Johnson, D. E. (1989), Analysis of Messy Data, Volume 2: Nonreplicated Experiments, Boca Raton, FL: Taylor & Francis Group.
Milliken, G. A., and Johnson, D. E. (2002), Analysis of Messy Data, Volume III: Analysis of Covariance, Boca Raton, FL: CRC Press LLC.
Milliken, G. A., and Johnson, D. E. (2009), Analysis of Messy Data, Volume 1: Designed Experiments (2nd ed.), Boca Raton, FL: Taylor & Francis Group, LLC.
Sinha, P. P. (2014), Bioinformatics with R Cookbook, Birmingham, UK: Packt Publishing Ltd.