Fabio E. Tonti

I sincerely hope that I don't sound like a LinkedIn reply guy: really really well put:)

I read and write, I explore and I question, I design and script and analyse, I interpret and communicate. I do this to train my mind in the hopes of one day generating new knowledge. New knowledge that might even be useful, and that no algorithm can yet be trained on.

I'm going to suggest this as reading to my students. I have been thinking about these issues a lot, @bharrap.bsky.social has written an impressively clear post synthesising multiple angles. Also credit to @hormiga.bsky.social, especially for his presenting his pov so transparently.

"This could just as easily be work for a student or early-career researcher. They’ll overcome the issue you’re having and will learn something about code, data management, analysis, and research in general."
He makes this point many times. We need to think about processes and medium-term outcomes.

Love this, it hits one of my biggest concerns with a lot of this stuff - i can appreciate how it can be useful for an expert to do things they may already know, sure, but what happens in 5/10/20 years after we cut off the talent development pipeline at the knees? The process is so so important

Remember when we stopped teaching maths after calculators were invented? Me neither.
Y‘all need to touch grass.

YouTube video by Josiah Parry Demystifying . . . (dots): R package dev fundamentals

Got a 10 minute video for you. The dots really clicked for me after watching this.

youtu.be/oIMFZf5dUFA?...

One of my graph has just entered the "best" section of the r-graph-gallery.com with a tutorial.

Featuring a waffle chart for time series, where the subtitle serves as a colorful legend.

Thanks a lot to @yan-holtz.bsky.social and @soeundataviz.bsky.social for adding it! #rstats #dataviz #ggplot2

Three things that are probably worth knowing about the 'Stanford top 2% scientists' metric that people are sharing.

1. It's based on a rather subjective 'C-score', where:

we need a word for a type of person who spends all their time working to live in a city so they can be near cool things, but they don't actually like going out

I met and made friends with a lot of people who are cooler and smarter than I am and it's pretty rad

Indeed!

Knowing ANOVA Lost in space WARNING. I know nothing about agriculture and even less about spatial statistics.

www.linkedin.com/pulse/knowin...

The Most Amazing Outdoor Archive Releases A Book There are three types of menswear books. The first are academic or academic-adjacent texts that explore subjects such as the...

They recently released a book of these archival images, along with essays about outdoor gear. We chatted how they built such an extraordinary collection, the surprising gaps in outdoor brands’ own histories, and what their work reveals about the culture of gear.

putthison.com/the-most-ama...

Maybe stupid q: what don't you like about your current solution?

Great stuff!

Very well written and interesting article, especially if you (like me) have only a superficial understanding of biology/chemistry.

Evidence-free, vibes-based analysis here. The other website literally suppresses links while boosting the vilest accounts. Just a bewildering degree of performative centrist brainrot here.

I strongly agree, what remains is the returning question: what's a good curriculum in stats/ds for applied peeps with not much formal background. Yeah. Remains frustrating.

I find this point very important, and try to repeat it to both students and colleagues over and over again.

Depends on whom you are teaching I suppose? Does every project in every field come with large sample size included?

An x/y plot with arrows spiraling outwards from the center. Everything is a shade of purple or white.

Adapted ggarrow to the new ggplot2 theme features!

```r
library(ggplot2)

ggplot(ggarrow::whirlpool(5), aes(x, y, group = group)) +
ggarrow::geom_arrow() +
theme_minimal(ink = "purple")
```
#ggplot2 #rstats

Exploring {ggplot2}’s Geoms and Stats – Stat’s What It’s All About

New blog post!

Ever wonder what geom_histogram is actually doing? How about geom_boxplot?

In celebration of the release of #ggplot2 4.0.0 (ggplot8?), I explore the relationships between the “geoms” and “stats” offered by the core {ggplot2} functions.

#rstats

How competition propels scientific risk-taking Kevin Gross∗ Department of Statistics North Carolina State University Raleigh, NC USA Carl T. Bergstrom† Department of Biology University of Washington Seattle, WA USA (Dated: September 9, 2025) In science as elsewhere, attention is a limited resource and scientists compete with one another to produce the most exciting, novel and impactful results. We develop a game-theoretic model to explore how such competition influences the degree of risk that scientists are willing to embrace in their research endeavors. We find that competition for scarce resources—for example, publications in elite journals, prestigious prizes, and faculty jobs—motivates scientific risk-taking and may be important in counterbalancing other incentives that favor cautious, incremental science. Even small amounts of competition induce substantial risk-taking. Moreover, we find that in an “opt-in” contest, increasing the stakes induces increased participation—which crowds the contest and further impels entrants to pursue higher-risk, higher-return investigations. The model also illuminates a source of tension in academic training and collaboration. Researchers at different career stages differ in their need to amass accomplishments that distinguish them from their peers, and therefore may not agree on what degree of risk to accept.

1. What does a Cold War-era game theory problem known as the silent duel have to do with high-risk research strategies, publication in Cell/Nature/Science glamor journals, and the academic job market?

Kevin Gross and I tackle these questions in our latest arXiv preprint: arxiv.org/abs/2509.06718

Hahaha that was too good...

Did you think you were a ggplot expert? Not any more!

[Seriously: congratulations, folks!! It looks like another big step]

An arrow with a LaTeX equation

Trigonometric functions and a unit circle

A bivariate change model with structured residuals

A hierarchical model of cognitive abilities

Now on CRAN, ggdiagram is a #ggplot2 extension that draws diagrams programmatically in #Rstats. Allows for precise control in how objects, labels, and equations are placed in relation to each other.
wjschne.github.io/ggdiagram/ar...

“Since about one year ago, many people have begun to think everything on ChatGPT is correct,” Vallata said. “It is not a tool for mountain advice, for routes, or for planning.”

Why Are the Italian Alps So Deadly This Summer? On average, three hikers have died every day throughout the summer in Italy’s high peaks. Experts explain why.

AI does appear to be rapidly accelerating human selection of the fittest….

except it’s doing it by straight-up killing people who rely on ChatGPT to plan dangerous trips, not by improving human cognition like the techbros want us to believe:

In my dept today we discussed deriving estimators from causal models. This can be opaque, but as a simple e.g. instrumental variable Z for estimating X on Y.

Z –a–> X –b–> Y, and X <– U –> Y, where U is unmeasured, a and b are path coefs. We want to know b. U prevents direct approach. >>