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ddarmon.github.io | ||
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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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debrouwere.org
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| | | | | [AI summary] A data scientist argues that traditional descriptive statistics like the mean and standard deviation are often poor choices for communicating data and recommends more interpretable alternatives like medians, percentiles, and visualizations. | |
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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| | | | | [AI summary] The author critiques the outdated, formula-heavy introductory statistics curriculum and outlines a plan for a new textbook that prioritizes practical skills, randomization methods, and a deeper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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matthewmcateer.me
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| | | Important mathematical prerequisites for getting into Machine Learning, Deep Learning, or any of the other space | ||