User:Timothee Flutre/Notebook/Postdoc/2011/11/16

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(About statistical modeling: add Udacity course)
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** "Statistical analysis and the illusion of objectivity" by Berger and Berry (American Scientist 1988, [http://dx.doi.org/10.1016/0278-2316(88)90057-6 DOI], [http://www.medicine.mcgill.ca/epidemiology/joseph/courses/EPIB-675/Berger.Berry.pdf pdf])
** "Statistical analysis and the illusion of objectivity" by Berger and Berry (American Scientist 1988, [http://dx.doi.org/10.1016/0278-2316(88)90057-6 DOI], [http://www.medicine.mcgill.ca/epidemiology/joseph/courses/EPIB-675/Berger.Berry.pdf pdf])
** "Bayesian methods: general background" by E. T. Jaynes (1985, free [http://bayes.wustl.edu/etj/articles/general.background.pdf pdf]) and "Where do we stand on maximum entropy?" by E. T. Jaynes (1978, free [http://bayes.wustl.edu/etj/articles/stand.on.entropy.pdf pdf])
** "Bayesian methods: general background" by E. T. Jaynes (1985, free [http://bayes.wustl.edu/etj/articles/general.background.pdf pdf]) and "Where do we stand on maximum entropy?" by E. T. Jaynes (1978, free [http://bayes.wustl.edu/etj/articles/stand.on.entropy.pdf pdf])
 +
** "The Philosophy of Statistics" by Lindley (JRSSD 2000, [http://dx.doi.org/10.1111/1467-9884.00238 DOI])
 +
** "What is statistics?" by Feinberg (An.Rev.Stat.Appl. 2014, [http://dx.doi.org/10.1146/annurev-statistics-022513-115703 DOI])
** "Mathematical Models and Reality: A Constructivist Perspective" by Christian Hennig (Foundations of Science 2010, [http://dx.doi.org/10.1007/s10699-009-9167-x DOI])
** "Mathematical Models and Reality: A Constructivist Perspective" by Christian Hennig (Foundations of Science 2010, [http://dx.doi.org/10.1007/s10699-009-9167-x DOI])
** "Philosophy and the practice of Bayesian statistics" by Andrew Gelman and Cosma Shalizi (British Journal of Mathematical and Statistical Psychology 2013, [http://dx.doi.org/10.1111/j.2044-8317.2011.02037.x DOI])
** "Philosophy and the practice of Bayesian statistics" by Andrew Gelman and Cosma Shalizi (British Journal of Mathematical and Statistical Psychology 2013, [http://dx.doi.org/10.1111/j.2044-8317.2011.02037.x DOI])

Revision as of 11:53, 6 April 2014

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About statistical modeling

  • intro courses:
    • "OpenIntro Statistics" by Diez, Barr and Cetinkaya-Rundel (free textbook)
    • "Statistics Done Wrong" by Alex Reinhart (free textbook)
    • "Mixed effects models for the population approach" by Marc Lavielle and the POPIX team at INRIA (free wiki)
    • "Graphical Models" by Zoubin Ghahramani (2012, free video & slides)
    • swirl, R package to learn stats and R simultaneously and interactively
  • advanced courses:
    • "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free book)
    • "A First Course in Bayesian Statistical Methods" by Peter Hoff (2010, book)
    • "Bayesian Data Analysis" by Andrew Gelman & co (2013, free slides, 3rd edition of the book)
    • "Statistical Decision Theory and Bayesian Analysis" by James Berger (1993, 2nd edition of the book)
  • mathematical aspects:
    • "Introduction to Linear Algebra" by Gilbert Strang (free videos, book)
    • "Matrix Differential Calculus with Applications in Statistics and Econometrics" by Magnus and Neudecker (2007, free pdf for the 3rd edition)
  • practical, computational aspects:
    • "How to share data with a statistician" by Jeff Leek (procedure on GitHub), see also the advice on genomics metadata by Raphael Irrizary and "statistical consulting" by Karl Broman (slides)
    • "Exploratory Data Analysis with R" by Jennifer Bryan (free course)
    • "Tutorial on Big Data with Python" by Marcel Caraciolo (free Python notebooks)
    • interpreted languages: obviously R, but more and more Python (SciPy for NumPy, Matplotlib, and pandas, but see also scikit-learn and statsmodels), as well as others (Julia)
    • C/C++: GSL, Armadillo, Eigen, Rcpp, Stan
    • editor: obviously Emacs (language-agnostic, org-mode, etc), but also Rstudio (R-only...) and IPython (Python-only...)
  • visualizing, plotting:
    • "Visualizing uncertainty about the future" by Spiegelhalter et al. (Science 2011, DOI)
    • "Let's practice what we preach: turning tables into graphs" by Gelman et al. (The American Statistician 2002, DOI)
    • "Top ten worst graphs" by Karl Broman (webpage)
    • "EDA: Investigate, Visualize, and Summarize Data Using Ra" (on Udacity, free courseware available)
  • philosophy, history, pragmatism:
    • "Statistical analysis and the illusion of objectivity" by Berger and Berry (American Scientist 1988, DOI, pdf)
    • "Bayesian methods: general background" by E. T. Jaynes (1985, free pdf) and "Where do we stand on maximum entropy?" by E. T. Jaynes (1978, free pdf)
    • "The Philosophy of Statistics" by Lindley (JRSSD 2000, DOI)
    • "What is statistics?" by Feinberg (An.Rev.Stat.Appl. 2014, DOI)
    • "Mathematical Models and Reality: A Constructivist Perspective" by Christian Hennig (Foundations of Science 2010, DOI)
    • "Philosophy and the practice of Bayesian statistics" by Andrew Gelman and Cosma Shalizi (British Journal of Mathematical and Statistical Psychology 2013, DOI)
    • "Statistical Inference : the Big Picture" by Robert Kass (Statistical Science 2011, DOI, free pdf on arXiv)
    • "In Praise of Simplicity not Mathematistry! Ten Simple Powerful Ideas for the Statistical Scientist" by Roderick Little (JASA 2013, DOI)
    • "Des spécificités de l’approche bayésienne et de ses justifications en statistique inférentielle" par Christian Robert (chapitre 2013, pdf gratuit sur HAL)
  • classics:
    • list from Christian Robert


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