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ddarmon.github.io | ||
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minireference.com
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| | | | | [AI summary] The author critiques the outdated, formula-heavy introductory statistics curriculum and outlines a plan for a new textbook that prioritizes practical skills, randomization methods, and a deeper conceptual understanding over rote memorization of analytical approximations. | |
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www.randomservices.org
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| | | | | [AI summary] The text covers various topics in probability and statistics, including continuous distributions, empirical density functions, and data analysis. It discusses the uniform distribution, rejection sampling, and the construction of continuous distributions without probability density functions. The text also includes data analysis exercises involving empirical density functions for body weight, body length, and gender-specific body weight. | |
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aurimas.eu
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| | | | | a.k.a. why you should (not ?) use uninformative priors in Bayesian A/B testing. | |
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gouthamanbalaraman.com
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| | | Discusses the convergence of the Monte-Carlo simulations of the Hull-White model | ||