#statstab #37 Collinearity isn’t a disease that needs curing

Thoughts: This shifted my thinking from "assumptions are nuisances to check" to understanding what they actually do and mean.

#MachineLearning #regression #stats #colinearity

janhove.github.io/posts/2019-0...

How have I never read this scathing paragraph about correlation coefficients from Tukey (1969) before? 🧪 #statistics

One of the big improvements in the new version of #ggplot2 are related to legends.

Teun van den Brand lays out all the detail in this blog post. Get ready for the legend extension extravaganza #stats

New species out! Exciting to participate in this paper describing new yellow-faced bees from the South Pacific. Like many of the Hawaiian Hylaeus, they tend to stay up in the forest canopy, which kept them hidden for a long time! Makes you wonder how many more are out there…
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Studying bee communities is critical to assessing their role in ecosystems and agricultural systems. A new meta-analysis of 72 bee-sampling studies reveals best practices—and the surprising breadth and scope necessary—for thoroughly documenting a local bee community.

Great resource for researchers who want to use #RStats for robust causal analysis. Helped me understand the logic behind DAGs (directed acyclic graphs): www.r-causal.org Thanks @malcolmbarrett.malco.io @lucystats.bsky.social & @travisgerke.bsky.social 🙏

A must read for ecologists. AIC is not appropriate when explanatory variables are correlated AND have independent effects on the response.

doi.org/10.1111/ele....

For anyone performing statistical analysis, in ecology or in any other field, this is incredibly relevant!

besjournals.onlinelibrary.wiley.com/doi/10.1111/...

#statstab #22 Plot model coefficients with {ggcoef_model()}

Thoughts: Very useful for quick plotting while drafting a write-up. Helper packages are good, but we can easily fall back into the cookbook method of stats.

#stats #dataviz #plots #rstats
larmarange.github.io/ggstats/arti...