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: 7. 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