Bibliografia

Principal

  • Linear models with R,2nd ed: Faraway,J.J. 2014 Chapman&Hall/CRC
  • The Elements of Statistical Learning: Data Mining, Inference,and Prediction.2nd ed: Hastie,T.,Tibshirani,R.and Friedam,J. 2009 Springer-Verlag, New York
  • Analysis of Variance in Experimental Design,2nd ed: Lindman,H.R. 2012 Springer New York
  • The Art of Data Science-A Guide for Anyone Who Works with Data: Peng,Roger D.,Matsui,E. 2018 PDFDRIVE
  • Regression Analysis:Theory,Methods, and Applications: Sen,A. and M.Srivastava 2012 Springer New York
  • Understanding Machine Learning: From Theory to Algorithms: Shalev-Shwartz, Shai and Ben-David, Shai 2014 Cambridge University Press
  • The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists: Shan, Carl; Wang, Henry; Song, Max and Chen, William 2015 Data Science Bookshelf
  • The Data Science Handbook: Advice and Insights from 25 Amazing Data Scientists: Shan, C., Wang, H., Song, M. and Chen, W. 2015 Data Science Bookshelf

Secundária

Não foi definida bibliografia secundária