It's important to emphasize that "realistic-looking" data does *not* mean "realistic" data – especially high-dimensional data (unfortunately that post doesn't warn against this).
If one had an algorithm that generated realistic data for a given inference problem, it would mean that that inference problem had been solved. So: for educational purposes, why not. But for validation-like purposes, use with uttermost caution and at your own peril.
I've finished an audiobook version of my #statistics textbook for biological and environmental sciences with #jamovi -- all free and available on my website and Spotify (https://bradduthie.github.io/audiobook.html). I initially underestimated how much my own students would want this, so my hope is that others my benefit from it. Please feel free to contact me if you're teaching an introductory statistics class and are looking for resources! #rstats #stats https://bradduthie.github.io/blog/statistics-audiobook-with-jamovi/
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I like the way this post explains the math behind statistical analyses of correlations with clear words and hand-drawn graphs. https://entropicthoughts.com/the-surprising-richness-of-correlations #statistics
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The Global Human Impact On Biodiversity
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https://doi.org/10.1038/s41586-025-08752-2 <-- shared paper
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#GIS #spatial #mapping #statistics #geostatistics #global #biodiversity #spatialanalysis #spatiotemporal #connected #systems #model #modeling #humanimpacts #environmenta; #ecosystems #habitat #pollution #climatechange #pressures #scale #homogenization #literature #diversity #conservation #sustainability
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Greg Cocks