#Tag
Understanding Probabilistic Computing with Clojure
#Probability #Statistics #MachineLearning #Clojure #Programming
I wrote out the whole exhausting narrative of what's happened at #UniversityOfNebraskaLincoln to the #statistics, #educational administration, #earth and #atmospheric sciences, and #textiles departments over the past 2.5 months, including the videos, the memes, and a fair bit of snark. https://srvanderplas.github.io/posts/other/unl-program-cuts-despair.html
The Board of Regents decides our fate in 2 days.
Understanding Probabilistic Computing with Clojure
#Probability #Statistics #MachineLearning #Clojure #Programming
I wrote out the whole exhausting narrative of what's happened at #UniversityOfNebraskaLincoln to the #statistics, #educational administration, #earth and #atmospheric sciences, and #textiles departments over the past 2.5 months, including the videos, the memes, and a fair bit of snark. https://srvanderplas.github.io/posts/other/unl-program-cuts-despair.html
The Board of Regents decides our fate in 2 days.
Why you shouldn't use listwise deletion when handling missing data. Video tutorial: https://www.youtube.com/watch?v=v9rzH0ACLZU
Check out my course on Missing Data Imputation in R, starting December 1: https://statisticsglobe.com/online-course-missing-data-imputation-r
🆕 blog! “Now witness the power of this fully operational Fediverse!”
How can you measure the popularity of a social network site? Perhaps by counting the number of active accounts, or the quality of the discourse, or even how many people reply to your witty memes.
Me? I prefer to look at how many people visit my blog…
👀 Read more: https://shkspr.mobi/blog/2025/11/now-witness-the-power-of-this-fully-operational-fediverse/
⸻
#ActivityPub #BlueSky #fediverse #mastodon #statistics
Actual causes of death in the US and media coverage of same.
And then we wonder why people have such a skewed understanding of the world.
ourworldindata.org is a treasure. Thanks, hannahritchie.bsky.social and colleagues.
https://ourworldindata.org/does-the-news-reflect-what-we-die-from
Why you shouldn't use listwise deletion when handling missing data. Video tutorial: https://www.youtube.com/watch?v=v9rzH0ACLZU
Check out my course on Missing Data Imputation in R, starting December 1: https://statisticsglobe.com/online-course-missing-data-imputation-r
🆕 blog! “Now witness the power of this fully operational Fediverse!”
How can you measure the popularity of a social network site? Perhaps by counting the number of active accounts, or the quality of the discourse, or even how many people reply to your witty memes.
Me? I prefer to look at how many people visit my blog…
👀 Read more: https://shkspr.mobi/blog/2025/11/now-witness-the-power-of-this-fully-operational-fediverse/
⸻
#ActivityPub #BlueSky #fediverse #mastodon #statistics
The PewResearch 2025 poll on Social Media use of adults in the US is out - and #Mastodon doesn't exist? 🤯
#PewResearch #Poll #Statistics #SocialMedia #Social #Tiktok #WhatsApp #Instagram #Bluesky #Threads #Facebook #Youtube #X #Twitter #Reddit #Snapchat #Graph #graphic #PewResearch #TruthSocial #news #Us #USA #Unitedstates #america #americans #results
R.A. Fisher wrote that the purpose of statisticians was "constructing a hypothetical infinite population of which the actual data are regarded as constituting a random sample." ( p. 311 here ). In The Zeroth Problem Colin Mallows wrote "As Fisher pointed out, statisticians earn their living by using two basic tricks-they regard data as being realizations of random variables, and they assume that they know an appropriate specification for these random variables."
Some of the pathological beliefs we attribute to techbros were already present in this view of statistics that started forming over a century ago. Our writing is just data; the real, important object is the “hypothetical infinite population” reflected in a large language model, which at base is a random variable. Stable Diffusion, the image generator, is called that because it is based on latent diffusion models, which are a way of representing complicated distribution functions--the hypothetical infinite populations--of things like digital images. Your art is just data; it’s the latent diffusion model that’s the real deal. The entities that are able to identify the distribution functions (in this case tech companies) are the ones who should be rewarded, not the data generators (you and me).
So much of the dysfunction in today’s machine learning and AI points to how problematic it is to give statistical methods a privileged place that they don’t merit. We really ought to be calling out Fisher for his trickery and seeing it as such.
#AI #GenAI #GenerativeAI #LLM #StableDiffusion #statistics #StatisticalMethods #DiffusionModels #MachineLearning #ML
Excellent article on the dangers of dichotomisation of continuous variables
“Cake causes herpes?” - promiscuous dichotomisation induces false positives
https://link.springer.com/article/10.1186/s12874-025-02712-0
R.A. Fisher wrote that the purpose of statisticians was "constructing a hypothetical infinite population of which the actual data are regarded as constituting a random sample." ( p. 311 here ). In The Zeroth Problem Colin Mallows wrote "As Fisher pointed out, statisticians earn their living by using two basic tricks-they regard data as being realizations of random variables, and they assume that they know an appropriate specification for these random variables."
Some of the pathological beliefs we attribute to techbros were already present in this view of statistics that started forming over a century ago. Our writing is just data; the real, important object is the “hypothetical infinite population” reflected in a large language model, which at base is a random variable. Stable Diffusion, the image generator, is called that because it is based on latent diffusion models, which are a way of representing complicated distribution functions--the hypothetical infinite populations--of things like digital images. Your art is just data; it’s the latent diffusion model that’s the real deal. The entities that are able to identify the distribution functions (in this case tech companies) are the ones who should be rewarded, not the data generators (you and me).
So much of the dysfunction in today’s machine learning and AI points to how problematic it is to give statistical methods a privileged place that they don’t merit. We really ought to be calling out Fisher for his trickery and seeing it as such.
#AI #GenAI #GenerativeAI #LLM #StableDiffusion #statistics #StatisticalMethods #DiffusionModels #MachineLearning #ML
Excellent article on the dangers of dichotomisation of continuous variables
“Cake causes herpes?” - promiscuous dichotomisation induces false positives
https://link.springer.com/article/10.1186/s12874-025-02712-0
A space for Bonfire maintainers and contributors to communicate
