Bibliografía

Corder, G. W., & Foreman, D. I. (2014). Nonparametric statistics: A step-by-step approach. John Wiley & Sons.

Deshpande, J. V., Naik-Nimbalkar, U., & Dewan, I. (2017). Nonparametric statistics: theory and methods. World Scientific.

Gomez Villegas, M. A. (2005). Inferencia estadística. Ediciones Díaz de Santos.

Bruce, P., Bruce, A., & Gedeck, P. (2020). Practical statistics for data scientists: 50+ essential concepts using R and Python. O’Reilly Media

Kelleher, J. D., & Tierney, B. (2018). Data science. MIT Press.

Ross, S. M. (2018). Introducción a la estadística. Reverté.

Wasserman, L. (2013). All of statistics: a concise course in statistical inference. Springer Science & Business Media.

Spiegel, M., & Stephens, L. (2009). Estadística–Serie Schaum. McGraw-Hill.

“Fundamentos de ciencia de datos con R” coordinado por Gema Fernández-Avilés y José-María Montero: https://cdr-book.github.io/

Weiss, N. A., & Weiss, C. A. (2017). Introductory statistics. London: Pearson.

“Estadística Aplicada a las Ciencias y la Ingeniería” escrito por Emilio L. Cano. https://emilopezcano.github.io/estadistica-ciencias-ingenieria/index.html

R for Data Science: https://r4ds.hadley.nz/eda Primera versión en castellano: https://es.r4ds.hadley.nz/

Bruce, P., Bruce, A., & Gedeck, P. (2020). Practical statistics for data scientists: 50+ essential concepts using R and Python. O’Reilly Media.

Fox, John, and Sanford Weisberg. 2018. An r Companion to Applied Regression. Sage publications.

Hao, Jiangang, and Tin Kam Ho. 2019. “Machine Learning Made Easy: A Review of Scikit-Learn Package in Python Programming Language.” Journal of Educational and Behavioral Statistics 44 (3): 348–61.

Hastie, Trevor, Robert Tibshirani, Jerome H Friedman, and Jerome H Friedman. 2009. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Vol. 2. Springer.

James, Gareth, Daniela Witten, Trevor Hastie, Robert Tibshirani, et al. 2013. An Introduction to Statistical Learning. Vol. 112. Springer.

Kelleher, John D, Brian Mac Namee, and Aoife D’arcy. 2020. Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies. MIT press.

Osmani, Addy. 2012. Learning JavaScript Design Patterns: A JavaScript and jQuery Developer’s Guide. " O’Reilly Media, Inc.".

Oualline, Steve. 2003. Practical c++ Programming. " O’Reilly Media, Inc.".

Tukey, John W et al. 1977. Exploratory Data Analysis. Vol. 2. Reading, MA.

Wirth, Rüdiger, and Jochen Hipp. 2000. “CRISP-DM: Towards a Standard Process Model for Data Mining.” In Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining, 1:29–39. Manchester.