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jakevdp.github.io | ||
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twiecki.io
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jaketae.github.io
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| | | | | So far on this blog, we have looked the mathematics behind distributions, most notably binomial, Poisson, and Gamma, with a little bit of exponential. These distributions are interesting in and of themselves, but their true beauty shines through when we analyze them under the light of Bayesian inference. In today's post, we first develop an intuition for conditional probabilities to derive Bayes' theorem. From there, we motivate the method of Bayesian inference as a means of understanding probability. | |
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austinrochford.com
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| | | | | For my day job, I spend a lot of time thinking about e-commerce analytics and cohort analysis in particular. Statistical age-period-cohort (APC) models are important in many fields such as epidemiolo | |
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dsaber.com
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| | | Why Even Try, Man? Irecently came upon Brian Granger and Jake VanderPlas's Altair, a promising young visualization library. Altair seems well-suited to addressing Python's ggplot envy, and its tie-in with JavaScript's Vega-Lite grammar means that as the latter develops new functionality (e.g., tooltips and zooming), Altair benefits -- seemingly for free! Indeed, I was so... | ||
