2020-04-19 Notes from my bubble

Bubble artifacts

These tweets and other artifacts from my sociology/statistics bubble caught my eyes recently. I’ll try to publish similar curations of my bubble regularly from now on.

Fooled by visualization

Kieran Healy and John Mullahy show data is interpreted differently depending on how one chooses the scales of their axes:

Prediction is hard

And of course it’s not just difficult to not get fooled from choices of vizualisation, but it’s also not easy at all to predict s-shaped curves, as Constanze Crozier shows.

Merkel explains R values

Also related: Merkel explains the R-value and its consequence for society. It’s rare to see politicians explain network analytical measures from epidemiology so fluently. With English subtitles:

Active learning for systematic reviews

Rens van de Schoot’s and Daniel Oberski’s team at the Methodology & Statistics Department of Utrecht University develop ASReview a wonderful tool which uses active learning to make systematic reviews easier. They even created a Covid-19 plugin. Cool stuff!

Robert Birkelbach
Scientific employee, doctoral student

My research interests include analytical sociology, social networks and, Bayesian statistics.


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