Bayesian statistics – Andrew Fairless, Ph.D.

What I Read: Bayesian Mixed Models

By Andrew Fairless on March 26, 2025December 8, 2024

https://towardsdatascience.com/evaluating-bayesian-mixed-models-in-r-python-27d344a03016?gi=e23f7abbacbf Evaluating Bayesian Mixed Models in R/PythonEduardo Coronado SrokaJul 3, 2020 “…model checking and evaluation are just one of those things you can’t (and shouldn’t) avoid… Yet, I think inContinue readingWhat I Read: Bayesian Mixed Models

What I Read: different meanings of p-value

By Andrew Fairless on June 7, 2023May 1, 2023

4 different meanings of p-value (and how my thinking has changed) 4 different meanings of p-value (and how my thinking has changed)Posted on April 14, 2023 9:14 AMAndrew Gelman “TheContinue readingWhat I Read: different meanings of p-value

What I Read: Generative Modeling by Estimating Gradients

By Andrew Fairless on March 7, 2022January 20, 2022

https://yang-song.github.io/blog/2021/score/ Generative Modeling by Estimating Gradients of the Data DistributionAuthor Yang SongDate May 5, 2021 “This blog post gives a detailed introduction to score-based generative models. We demonstrate that thisContinue readingWhat I Read: Generative Modeling by Estimating Gradients

What I Read: Bayesian and frequentist results

By Andrew Fairless on May 21, 2021May 1, 2021

https://www.allendowney.com/blog/2021/04/25/bayesian-and-frequentist-results-are-not-the-same-ever/ Bayesian and frequentist results are not the same, everApril 25, 2021Allen Downey “You can’t compare results from Bayesian and frequentist methods because the results are different kinds of things….Continue readingWhat I Read: Bayesian and frequentist results

What I Read: Statistics, Geometry Problem

By Andrew Fairless on April 6, 2021March 22, 2021

https://www.quantamagazine.org/statistics-postdoc-tames-decades-old-geometry-problem-20210301/ Statistics Postdoc Tames Decades-Old Geometry ProblemTo the surprise of experts in the field, a postdoctoral statistician has solved one of the most important problems in high-dimensional convex geometry.Erica KlarreichMarchContinue readingWhat I Read: Statistics, Geometry Problem

What I Read: Bayesian Hierarchical Modelling at Scale

By Andrew Fairless on April 2, 2021March 21, 2021

https://florianwilhelm.info/2020/10/bayesian_hierarchical_modelling_at_scale/ Finally! Bayesian Hierarchical Modelling at ScaleFlorian WilhelmDate Oct. 01, 2020 “In this blog post, I want to draw your attention to the somewhat dusty Bayesian Hierarchical Modelling. Modern techniquesContinue readingWhat I Read: Bayesian Hierarchical Modelling at Scale

What I Watch: The medical test paradox, Can redesigning Bayes rule help?

By Andrew Fairless on February 28, 2021February 27, 2021

https://youtu.be/lG4VkPoG3ko The medical test paradox: Can redesigning Bayes rule help?Dec 22, 20203Blue1Brown “In short, an accurate test is not necessarily a predictive test… of all of the places for mathContinue readingWhat I Watch: The medical test paradox, Can redesigning Bayes rule help?

What I Read: Think Like an Epidemiologist

By Andrew Fairless on January 16, 2021December 24, 2020

https://www.nytimes.com/2020/08/04/science/coronavirus-bayes-statistics-math.html How to Think Like an EpidemiologistDon’t worry, a little Bayesian analysis won’t hurt you.By Siobhan RobertsAug. 4, 2020Updated 4:57 p.m. ET “Observing early research in March about how theContinue readingWhat I Read: Think Like an Epidemiologist

What I Read: A winner’s curse adjustment

By Andrew Fairless on January 10, 2021December 23, 2020

http://www.erikdrysdale.com/winners_curse/ Erik DrysdalebioeconometRicianAbout Recent Posts ShinyApps CVA winner’s curse adjustment for a single test statistic “One consequence of using frequentist statistical tools to conduct scientific inference is that effect sizesContinue readingWhat I Read: A winner’s curse adjustment

What I Watch: Bayes theorem

By Andrew Fairless on November 28, 2020November 28, 2020

Bayes theoremDec 22, 20193Blue1Brown “The goal is for you to come away from this video understanding one of the most important formulas in all of probability: Bayes theorem.”

Tag: Bayesian statistics