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About statistical modeling
- great courses:
- "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free online book)
- "A First Course in Bayesian Statistical Methods" by Peter Hoff (book)
- "Bayesian Data Analysis" by Andrew Gelman (free online slides)
- mathematical aspects:
- "Intro to Linear Algebra" by Gilbert Strang
- "Multivariate Calculus" by Magnus and Neudecker
- practical, computational aspects:
- "Exploratory Data Analysis with R" by Jennifer Bryan (free online course)
- editor: Emacs
- interpreted languages: R, Python and others (Julia?)
- C/C++: GSL, Armadillo, Eigen, Rcpp
- visualizing, plotting:
- "Visualizing uncertainty about the future" by Spiegelhalter, et al. (Science 2011, DOI)
- "Let's practice what we preach: turning tables into graphs": Gelman et al (The American Statistician 2002, DOI)
- philosophy, history:
- Christian Hennig
- Andrew Gelman and Cosma Shalizi
- Christian Robert
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