I am here for all interesting and funny posts on the social sciences, broadly understood and including open science and meta science, academia, teaching and research. https://linktr.ee/ingorohlfing
Reposted by Mark Rubin, Ingo Rohlfing, Madeleine Pownall
Reposted by Dorothy Bishop, Ingo Rohlfing
Can you see the problem?
Reposted by Ingo Rohlfing
the unthinking use of one technique with that of another."
A.P.Grieve (1992) Royal Statistical Society News and Notes, 18(7), 3-4.
Reposted by Ingo Rohlfing
128 color combinations from mixing 7 colors
moebio.com/research/sev...
Reposted by Ingo Rohlfing, Andrew Livingstone
Reposted by Ingo Rohlfing
🔹Applications of Focus Groups @karenlumsden.bsky.social
🔹Case Study Research: Method & Practice @ingorohlfing.bsky.social
🔹Intro to Qualitative Comparative Analysis
📆 16–27 Feb 2026, Online
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#ecprms
Reposted by Robbert Sanderman, Mikael Ehn, Seema Jayachandran , and 12 more Robbert Sanderman, Mikael Ehn, Seema Jayachandran, Alexander Wuttke, Marno Verbeek, Cathy N. Davidson, Jennifer Clark, Ingo Rohlfing, Paolo Crosetto, Bessma Momani, David J. Berri, Dolly Jørgensen, Larry W. Hunter, Kathleen Kennedy, Giulio Mattioli
Reposted by Jason N. Doctor, Ingo Rohlfing
* p values are highly unrealiable - don't trust them, don't use them!
www.thenewstatistics.com
tiny.cc/osfsigroulette
#IRICSydney
Of course...
Reposted by Ingo Rohlfing, Roopika Risam, Annette Yoshiko Reed
Reposted by Martin Paul Eve, Ingo Rohlfing
Of course...
The tabs seem a bit overloaded to me with input elements, data, formulas and plots, but this is just my personal impression.
Here is the direct link to the website: 2k1.iq.harvard.edu 2/
Reposted by Sebastian Karcher
www.cambridge.org/core/journal...
I think this is a very useful approach when one does not want to teach coding in parallel. Simulating data and quantities of interest are insightful features, though at the expense of not using 1/
Reposted by Ingo Rohlfing, Ian Hussey
I was referring to a post where someone wrote he "heard numbers" that a larger share of papers is never read and an even larger share never cited. There was no source. One should just not dish out such number w/o sources.
Maybe I am missing something here: this seems to overdo it with exploring AI 1/
Early career scholars are desperate to get more papers to compete in the academic job market. This can make it hard for faculty mentors hard to reduce their output unless they shrink their lab (which removes opportunities from next generation).
Reposted by Ingo Rohlfing, Madeleine Pownall, Rachel S. Franklin
Early career scholars are desperate to get more papers to compete in the academic job market. This can make it hard for faculty mentors hard to reduce their output unless they shrink their lab (which removes opportunities from next generation).
If you pay Nature € 10.690, they will publish this in Nature Ageing.
I can tell you what I think of that for free.
www.nature.com/articles/s43...