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: degree certainty

By Andrew Fairless on February 24, 2025November 9, 2024

https://blog.alexalemi.com/a-degree-of-certainty.html A Degree of CertaintyAlexander A. Alemi2024-08-14 “None of the common ways to measure proabilities are statistically uniform. What do I mean by this? Not all 1% changes in probabilityContinue readingWhat I Read: degree certainty

What I Read: probability generating

By Andrew Fairless on February 20, 2025November 9, 2024

https://entropicthoughts.com/probability-generating-functions Probability-Generating FunctionsChris2024-10-29 “I have long struggled with understanding what probability-generating functions are and how to intuit them. There were two pieces of the puzzle missing for me, and we’llContinue readingWhat I Read: probability generating

What I Read: myths, randomisation

By Andrew Fairless on February 18, 2025November 9, 2024

https://www.bps.org.uk/psychologist/dispelling-myths-about-randomisation Dispelling myths about randomisation14 October 2024 “The first myth is that randomisation works because it balances confounders…. This leads to the second myth, which is that we should testContinue readingWhat I Read: myths, randomisation

What I Read: Sampling, SQL

By Andrew Fairless on February 17, 2025October 25, 2024

https://blog.moertel.com/posts/2024-08-23-sampling-with-sql.html Sampling with SQLTom MoertelAugust 23, 2024 “Sampling is one of the most powerful tools you can wield to extract meaning from large datasets…. If you know how to takeContinue readingWhat I Read: Sampling, SQL

What I Read: Gaussians

By Andrew Fairless on February 13, 2025October 25, 2024

https://gestalt.ink/gaussians Understanding Gaussians “The Gaussian distribution, or normal distribution is a key subject in statistics, machine learning, physics, and pretty much any other field that deals with data and probability.”

What I Read: Bounded Kernel Density Estimation

By Andrew Fairless on February 4, 2025October 25, 2024

https://towardsdatascience.com/bounded-kernel-density-estimation-2082dff3f47f Bounded Kernel Density EstimationThomas RouchFeb 28, 2024 “…when it comes to estimating continuous densities, people often resort to treating it as a mysterious black box. However, understanding this conceptContinue readingWhat I Read: Bounded Kernel Density Estimation

What I Read: Statistical Validity, Clusters

By Andrew Fairless on January 29, 2025October 19, 2024

https://www.fharrell.com/post/cluster The Burden of Demonstrating Statistical Validity of ClustersFrank HarrellOctober 6, 2024 “Most medical applications of statistical clustering techniques fail to address the most basic questions…”

What I Read: Stein’s Paradox

By Andrew Fairless on January 28, 2025October 19, 2024

https://towardsdatascience.com/steins-paradox-ba493f46e181?gi=32a9546d7b85 Stein’s Paradox: Why the Sample Mean Isn’t Always the BestTim SumnerSep 30, 2024 “…Stein’s theorem showed that when estimating three or more parameters simultaneously… biased estimators can outperform theContinue readingWhat I Read: Stein’s Paradox

What I Read: Data Missing

By Andrew Fairless on January 22, 2025October 19, 2024

https://www.quantamagazine.org/when-data-is-missing-scientists-guess-then-guess-again-20241002/ When Data Is Missing, Scientists Guess. Then Guess Again.Matt von HippelOctober 2, 2024 “Across the social and biological sciences, statisticians use a technique that leverages randomness to deal withContinue readingWhat I Read: Data Missing

Tag: statistics