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## About statistical modeling

• intro courses:
• "OpenIntro Statistics" by Diez, Barr and Cetinkaya-Rundel (free textbook)
• "Mixed effects models for the population approach" by Marc Lavielle and the POPIX team at INRIA (free wiki)
• "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free book)
• "A First Course in Bayesian Statistical Methods" by Peter Hoff (book)
• "Bayesian Data Analysis" by Andrew Gelman (free slides, book)
• "Statistical Decision Theory and Bayesian Analysis" by James Berger (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 (free pdf, book)
• practical, computational aspects:
• "How to share data with a statistician" by Jeff Leek (procedure on GitHub), see also "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)
• philosophy, history, pragmatism:
• "Where do we stand on maximum entropy?" by E. T. Jaynes (1978, free pdf)
• "Mathematical Models and Reality: A Constructivist Perspective" by Christian Hennig (Foundations of Science 2007, 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