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[Joachim Schork @JoachimSchork]

If you're still using raw R outputs for presentations, it's time for an upgrade! Tools like gtsummary bring your statistical results to life, making them much more digestible for non-technical audiences.

While base R functions like summary(fit) work well for statisticians, they can be too complex for stakeholders who aren’t familiar with the detailed output. The tbl_regression() function from gtsummary makes it easy to present regression results clearly.

In addition, gtsummary is highly versatile - it’s not just limited to linear regression. You can apply it to generalized linear models, survival analyses, and more. The package even allows you to include p-values, confidence intervals, and other important statistics directly within the tables, helping you to better communicate statistical results.

Here are a few standout benefits:
✅ Simplified output that’s easier for stakeholders to understand
✅ Works seamlessly with a variety of models
✅ Customizable tables with key statistics like p-values, confidence intervals, and more

The visualization included here was originally shared in a recent post by Dr. Alexander Krannich.

#rstats #gtsummary #statistics #datascience

[Thorben Danke @sagaOptics]

🇬🇧Fruitfly with mite. Mounting fruit flies is almost an almost impossible task for me, you know how small they are. And then there are even smaller mites that make themselves comfortable on the fly. The mite on the dead found fly from the windowsill was still alive, I only needed three attempts here until it sat still for a few minutes.

🇩🇪Fruchtfliege mit Milbe. Die Fruchtfliegen zu präparieren ist schon fast eine kaum zu lösende Aufgabe für mich, ihr wisst wie klein die sind. Und dann gibt’s da noch kleineren Milben, welche es sich auf der Fliege gemütlich machen. Die Milbe auf dem Totfund von der Fensterbank war noch lebendig, hier habe ich nur drei Anläufe benötigt bis sie mal eine paar Minuten still saß.

#fruitfly #mite #insects #entomology #macrophotography #diptera

[Les Flores @lesssflo]

Hola, te comparto código #R para obtener #correlación: #Pearson si tus datos son normales y cuantitativos o #Spearman y #Kendall si tus datos son ordinales: https://t.co/GaSE2xKLPH

También puedes revisar esta página sobre correlación: https://t.co/jw0qDGGx22

[Matt Dancho (Business Science) @mdancho84]

This book singlehandedly 10X-ed my Data Science knowledge.

An Introduction to Statistical Learning with Applications in R (ISLR).

Let's dive in: