User:Timothee Flutre/Notebook/Postdoc/2011/11/16
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(→About statistical modeling: add links to society) 
(→About statistical modeling: add openintro) 

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==About statistical modeling==  ==About statistical modeling==  
  * '''  +  * '''courses''': 
** "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free [http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ book])  ** "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free [http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ book])  
** "A First Course in Bayesian Statistical Methods" by Peter Hoff ([http://www.amazon.com/gp/product/0387922997 book])  ** "A First Course in Bayesian Statistical Methods" by Peter Hoff ([http://www.amazon.com/gp/product/0387922997 book])  
** "Bayesian Data Analysis" by Andrew Gelman (free [http://www.stat.columbia.edu/~gelman/book/slides slides], [http://www.amazon.com/dp/1439840954 book])  ** "Bayesian Data Analysis" by Andrew Gelman (free [http://www.stat.columbia.edu/~gelman/book/slides slides], [http://www.amazon.com/dp/1439840954 book])  
** "Mixed effects models for the population approach" by Marc Lavielle and the POPIX team at INRIA (free [http://popix.lixoft.net/index.php?title=Home_page wiki])  ** "Mixed effects models for the population approach" by Marc Lavielle and the POPIX team at INRIA (free [http://popix.lixoft.net/index.php?title=Home_page wiki])  
+  ** "OpenIntro Statistics" by Diez, Barr and CetinkayaRundel (free [http://www.openintro.org/stat/textbook.php textbook])  
* '''mathematical aspects''':  * '''mathematical aspects''':  
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* '''practical, computational aspects''':  * '''practical, computational aspects''':  
  ** "How to share data with a statistician" by Jeff Leek (free on [https://github.com/jtleek/datasharing  +  ** "How to share data with a statistician" by Jeff Leek (free on [https://github.com/jtleek/datasharing procedure] on GitHub) 
** "Exploratory Data Analysis with R" by Jennifer Bryan (free [http://www.stat.ubc.ca/~jenny/STAT545A/2012lectures/ course])  ** "Exploratory Data Analysis with R" by Jennifer Bryan (free [http://www.stat.ubc.ca/~jenny/STAT545A/2012lectures/ course])  
** "Tutorial on Big Data with Python" by Marcel Caraciolo (free Python [https://github.com/marcelcaraciolo/bigdatatutorial notebooks])  ** "Tutorial on Big Data with Python" by Marcel Caraciolo (free Python [https://github.com/marcelcaraciolo/bigdatatutorial notebooks])  
** interpreted languages: obviously [http://openwetware.org/wiki/User:Timothee_Flutre/Notebook/Postdoc/2011/11/07 R], but more and more Python ([http://www.scipy.org/ SciPy] for NumPy, IPython, Matplotlib, and pandas, but also [http://scikitlearn.org/ scikitlearn] and [http://statsmodels.sourceforge.net/ statsmodels]), as well as others (Julia?)  ** interpreted languages: obviously [http://openwetware.org/wiki/User:Timothee_Flutre/Notebook/Postdoc/2011/11/07 R], but more and more Python ([http://www.scipy.org/ SciPy] for NumPy, IPython, Matplotlib, and pandas, but also [http://scikitlearn.org/ scikitlearn] and [http://statsmodels.sourceforge.net/ statsmodels]), as well as others (Julia?)  
** C/C++: [http://en.wikipedia.org/wiki/GNU_Scientific_Library GSL], [http://en.wikipedia.org/wiki/Armadillo_%28C++_library%29 Armadillo], [http://en.wikipedia.org/wiki/Eigen_(C%2B%2B_library) Eigen], [http://www.rcpp.org/ Rcpp], [http://mcstan.org/ Stan]  ** C/C++: [http://en.wikipedia.org/wiki/GNU_Scientific_Library GSL], [http://en.wikipedia.org/wiki/Armadillo_%28C++_library%29 Armadillo], [http://en.wikipedia.org/wiki/Eigen_(C%2B%2B_library) Eigen], [http://www.rcpp.org/ Rcpp], [http://mcstan.org/ Stan]  
  ** editor: [https://openwetware.org/wiki/User:Timothee_Flutre/Notebook/Postdoc/2012/07/25 Emacs]  +  ** editor: obviously [https://openwetware.org/wiki/User:Timothee_Flutre/Notebook/Postdoc/2012/07/25 Emacs] (languageagnostic, orgmode, etc) 
* '''visualizing, plotting''':  * '''visualizing, plotting''':  
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** "Statistical Inference : the Big Picture" by Robert Kass (Statistical Science 2011, [http://dx.doi.org/10.1214/10STS337 DOI], free [http://arxiv.org/pdf/1106.2895v2.pdf pdf] on arXiv)  ** "Statistical Inference : the Big Picture" by Robert Kass (Statistical Science 2011, [http://dx.doi.org/10.1214/10STS337 DOI], free [http://arxiv.org/pdf/1106.2895v2.pdf pdf] on arXiv)  
** "In Praise of Simplicity not Mathematistry! Ten Simple Powerful Ideas for the Statistical Scientist" by Roderick Little (JASA 2013, [http://dx.doi.org/10.1080/01621459.2013.787932 DOI])  ** "In Praise of Simplicity not Mathematistry! Ten Simple Powerful Ideas for the Statistical Scientist" by Roderick Little (JASA 2013, [http://dx.doi.org/10.1080/01621459.2013.787932 DOI])  
  ** "Des spécificités de l’approche bayésienne et de ses justifications en statistique inférentielle"  +  ** "Des spécificités de l’approche bayésienne et de ses justifications en statistique inférentielle" par Christian Robert (chapitre 2013, [http://hal.archivesouvertes.fr/docs/00/87/01/24/PDF/Bayes.pdf pdf] gratuit sur HAL) 
* '''classics''':  * '''classics''': 
Revision as of 00:44, 4 December 2013
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About statistical modeling
