Marcos Fanton

Looking forward to talking to @tricksterprince.bsky.social about my new book Keeping Hold: A Cultural and Social History of Possession at 1pm today!

Interactive resources With the power of OJS and Quarto, I’ve created a few interactive websites to illustrate trickier statistical concepts when teaching. Check them out (and adapt and copy as much as you want!) With links to three different websites (accessible at the main link in the post)

Finally got around to adding fancy links to my different interactive teaching websites for showing things like p-hacking, p-value interpretations, and (still-in-draft-form) DAGs at www.andrewheiss.com/teaching/ #rstats #QuartoPub #statsky

AI Translations Are Adding ‘Hallucinations’ to Wikipedia Articles AI translated articles swapped sources or added unsourced sentences with no explanation, while others added paragraphs sourced from completely unrelated material.

NEW: Wikipedia editors have implemented new policies and restricted a number of contributors who were paid to use AI to translate existing Wikipedia articles into other languages after they discovered these AI translations added AI “hallucinations,” or errors, to the resulting article.

There is an alternative fully-Frequentist interpretation of confidence intervals that more closely connects them to the idea of null-hypothesis significance testing. The 95% confidence interval contains all possible population parameters that, if they were our null hypothesis, would not be rejected with an alpha of .05 because of our data.[8] One could shorten this to “the confidence interval contains all parameter values that we cannot reject” or “the confidence interval contains all parameter values that are compatible with the data.” The appeal of this is that it’s more snappy than any statement about coverage, while not being wrong according to Frequentist logic. It also does feel like an explanation, although when you think about it, it assumes that you have understood null hypothesis significance testing, and null hypothesis significance testing is confusing in its own right. If you can just assume that people have understood this one complicated thing, can’t you just assume that they have also understood confidence intervals and don’t need any interpretation at all? Then again, if you are deeply confused about the whole matter, maybe this is an elegant solution that buries any confusion one level deeper, where it won’t upset people who really care about confidence intervals.

Confidence interval interpretation is a lot of “security from criticism by obscurity”, in the appendix of our blog post (www.the100.ci/2024/12/05/w...) we also cover this biblically accurate interpretation:

economista faz filho?

ninguém mais está a salvo do chatgpt e do som alto dos reels do instagram.

African Philosophy and the Politics of Food Systems This open access book argues food systems need to be questioned on ethical, epistemic grounds and posits African philosophy as valuable source in doing so

Proud that our book “African Philosophy and the Politics of Food Systems” is out & Open Access. It’s a collective effort of showing that African philosophy is more than an academic subfield but of central importance for shaping futures on the continent. link.springer.com/book/10.1007...

David Lynch saying ‘One day, the sadness will end. But I don’t think today’s the day.’

It’s really worth to read the @quantamagazine.bsky.social piece on Goos discovery of what Ferreirós told us 30 years ago, and Emmy Noether helped to find out #infinity #mathematics #history #plagiarism #coisadehomem

www.quantamagazine.org/the-man-who-...

cuidado! ⛔️

still frame from the beginning of Twin Peaks it is February 24th and Special Agent Dale Cooper arrived in the town of Twin Peaks

Good morning

Hello, dplyr 1.2.0! Join us with Davis Vaughan to explore new functions! Tuesday, Feb 24 at 12pm ET pos.it/dslab

I'm beyond excited for tomorrow's Data Science Lab with @davisvaughan.bsky.social!

dplyr 1.2.0 is now out. There are many new functions in this release, and you will see them in action, live. You won't want to `filter_out()` this info 😉

Join us, we can't `replace_*` you 🧡 pos.it/dslab

homem com camisa azul fazendo sinal de paz-e-amor com o boneco de Olinda O Invejado

me protegendo de mau-olhado

6 anos sem comer mungunzá, manuê, sapoti. Água de coco gelada todo dia. que coisa bem boa!

saudades quando tudo era blog

Race and the Early Modern — CEMS KCL Blog

Delighted to announce our seminar - 'Race and the Early Modern' - now has a full schedule of events. We'll be convening monthly to discuss research on race, racemaking, and racialisation across #earlymodern studies.

@kingsartshums.bsky.social @folger.edu

kingsearlymodern.co.uk/race-and-the...

This is one of the most important cases that galvanized Black people in the late 40s through the 1950s. Almost every major Black leader had a comment about it. It is also one of the most successful defense committees that was organized in the 20th century. Almost no one knows about it today.

This is a good post! I keep using 1234 or 12345, but only for visualization stuff like jittering. For real stuff, I go to random dot org (based on atmospheric noise) and create a random 8+ digit integer, generally one for each brms model I run in a project

Industry Influence in High-Profile Social Media Research To what extent is social media research independent from industry influence? Leveraging openly available data, we show that half of the research published in top journals has disclosable ties to indus...

Who is the Big Tobacco of today?
In new work, we find 50% of high profile social media papers are connected to big tech through funding, collaboration and employment. Most connections aren't disclosed. @jbakcoleman.bsky.social @jevinwest.bsky.social @carlbergstrom.com 1
arxiv.org/abs/2601.11507

Logo of the Open Visualization Academy, designed by Vinicius Sueiro

The Open Visualization Academy launches on FRIDAY! openvisualizationacademy.org

More information in our newsletter: openvisualizationacademy.beehiiv.com/p/the-open-v...

#dataViz #dataVisualization #infographics #dataJournalism

**Part 1: From Bayesian inference to Bayesian workflow** 1. Bayesian theory and Bayesian practice 2. Statistical modeling and workflow 3. Computational tools 4. Introduction to workflow: Modeling performance on a multiple choice exam **Part 2: Statistical workflow** 5. Building statistical models 6. Using simulations to capture uncertainty 7. Prediction, generalization, and causal inference 8. Visualizing and checking fitted models 9. Comparing and improving models 10. Statistical inference and scientific inference **Part 3: Computational workflow** 11. Fitting statistical models 12. Diagnosing and fixing problems with fitting 13. Approximate algorithms and approximate models 14. Simulation-based calibration checking 15. Statistical modeling as software development

**4. Case studies** 16. Coding a series of models: Simulated data of movie ratings 17. Prior specification for regression models: Reanalysis of a sleep study 18. Predictive model checking and comparison: Clinical trial 19. Building up to a hierarchical model: Coronavirus testing 20. Using a fitted model for decision analysis: Mixture model for time series competition 21. Posterior predictive checking: Stochastic learning in dogs 22. Incremental development and testing: Black cat adoptions 23. Debugging a model: World Cup football 24. Leave-one-out cross validation model checking and comparison: Roaches 25. Model building and expansion: Golf putting 26. Model building with latent variables: Markov models for animal movement 27. Model building: Time-series decomposition for birthdays 28. Models for regression coefficients and variable selection: Student grades 29. Sampling problems with latent variables: No vehicles in the park 30. Challenge of multimodality: Differential equation for planetary motion 31. Simulation-based calibration checking in model development workflow **Appendices** A. Statistical and computational workflow for Bayesians and non-Bayesians B. How to get the most out of Bayesian Data Analysis

Bayesian Workflow by
Andrew Gelman, Aki Vehtari, @rmcelreath.bsky.social with @danpsimpson.bsky.social, @charlesm993.bsky.social, @yulingy.bsky.social, Lauren Kennedy, Jonah Gabry, @paulbuerkner.com, @modrakm.bsky.social, @vianeylb.bsky.social

(in production, estimated copy-editing time 6 weeks)

Os camaleões de Madeleine de Scudéry Descrever a natureza e a cultura no século XVII

Pesquisei e traduzi “História de dois camaleões” da escritora seiscentista francesa Madeleine de Scudéry. Aqui vão algumas impressões teóricas e estilísticas do texto:

impossível não ser brasileiro

R code to create default ggplot2 scatter plot of mpg against wt with mtcars data

Did you know that you can edit a #ggplot2 chart after it's been created without having to rewrite the original #RStats code?

Let's say we've made a scatter plot with this code...

Alceu Valença : Tiny Desk Brasil YouTube video by Tiny Desk Brasil

22min03s de puro amor.
www.youtube.com/watch?v=T1yc...

Comentários de Catarina Dutilh Novaes (@cdutilhnovaes.bsky.social) , Eros Carvalho (@filosofemas.bsky.social), Sarita Albagli e Ulysses Albuquerque.

Dia 10.02, Pedro (@93pedrobravo.bsky.social) e eu estaremos organizando um book symposium sobre o livro Transformative Transdisciplinarity, de D. Ludwig ( @davidludwig.bsky.social) e C. El-Hani. O livro é maravilhoso. Não deixem de se inscrever pelo link: bit.ly/4jtM3rD.

Airing my grievances with wellbeing science We have a streetlight problem

if i could make you read ONE (1) single post to improve your understanding of the challenges of social science in general it would be this one from @markfabian.bsky.social about wellbeing science specifically

profmarkfabian.substack.com/p/airing-my-...

Explaining Famine in the British Empire: Agricultural Science, Food Security, and the Rise of Statistics Abstract. This book is about the famines and food shortages that struck India and Britain at the close of the eighteenth century, and it explores how these

My book is out and is open access!

academic.oup.com/book/61892