🎲 Online course: Introduction to Bayesian Data Analysis in R 🗓 24–26 June 2026 Bayesian inference, MCMC with brms/Stan, linear models, GLMs, mixed effects, model comparison. https://www.ntu.ac.uk/course/short-courses/social-sciences/1.-introduction-to-bayesian-data-analysis-using-r-online

🔢 Online course: Multilevel & Mixed Effects Models in R 🗓 10–11 June 2026 Regression for hierarchical data: random intercepts & slopes, nested/crossed structures. https://www.ntu.ac.uk/course/short-courses/social-sciences/introduction-to-multilevel-and-mixed-effects-models-using-r-online

📈 Online course: Generalised Linear Models in R 🗓 27–28 May 2026 Regression for non-normal data: logistic (binary, ordinal, multinomial), Poisson, neg-binomial, zero-inflated etc. https://www.ntu.ac.uk/course/short-courses/social-sciences/introduction-to-generalized-linear-models-in-r2

📊 Online course: Introduction to Statistics Using R and RStudio 🗓 13–14 May 2026 Hands-on intro to R & RStudio (including tidyverse, RMarkdown, and core statistics). https://www.ntu.ac.uk/course/short-courses/social-sciences/introduction-to-statistics-using-r-and-rstudio-online

Happy to share that my first solo-authored paper is now published in the Annual Review of Statistics and Its Application. 📑 Reproducibility in the Classroom 🔗 www.annualreviews.org/content/jour...

On 12th March 2025 (3pm-5pm, UK time), @rss-teach.bsky.social and TALMO will be hosting an online event on *Teaching Open, Transparent, and Reproducible Data Analysis*. See talmo.uk/2025/dataana.... Free and open to all. 1/2

New updated slide deck of my talk "rage against the machine learning" www.slideshare.net/slideshow/ra...

{effectsize} version 1.0.0 has been released! 🍕👹 Not many changes in this update, but his is quite a milestone 🥳 - the second stable package from @easystats.bsky.social, with more to come soon! #rstats easystats.github.io/effectsize/

We are excited to announce pal: a package of ergonomic #LLM assistants designed to help you complete repetitive tasks quickly in RStudio or Positron! Created by @simonpcouch.com, the documentation walks through built-in pals and how to make your own: simonpcouch.github.io/pal/ #RStats

The BPS Statistics and Research Methods Advisory Panel is a panel of academic researchers who advise editors and provide stats or research methods related peer review for BPS journals. The Panel is currently recruiting for new members. www.bps.org.uk/bps-statisti...

For those who love LLMs, especially open-source LLMs, here is a very useful and up to date list: github.com/allenai/awes...

The source I now most frequently refer to in my peer reviews: datamgmtinedresearch.com/document#doc... Documenting things is hard but people really can't check/use your work if it doesn't have some docs. We can do better!

Interact with Bluskey in R using the atrrr package. E.g, get your followers and followees: library(atrrr) my_handle <- 'username' auth(user = my_handle, password = 'password') my_followers <- get_followers(actor = my_handle, limit = Inf) my_followees <- get_follows(actor = my_handle, limit = Inf)

S7 0.2.0 is now on CRAN, thanks primarily to the hard work of @t-kalinowski.bsky.social. S7 is a collaborative effort to supersede S3 and S4 and you can read all about it (and what's new in 0.2.0) at www.tidyverse.org/blog/2024/11... #rstats

You can open any high quality medical journal and read authors talking about "trends" in estimates, almost always when the attached p-value is just outside the "significance" cutoff. This kind of thing is maddening, because it simply doesn't reflect reality. It's not just wrong, it's...stupid 😬. 1/