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Input feed: Statistical Modeling, Causal Inference, and Social Science

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Oregon State Stats Dept. is Hiring

https://statmodeling.stat.columbia.edu/2024/11/13/oregon-state-stats-dept-is-hiring/

Statistical Modeling, Causal Inference, and Social Science 11/13/2024

jobs
Make a hypothesis about what you expect to see, every step of the way. A manifesto:

https://statmodeling.stat.columbia.edu/2024/11/13/make-a-hypothesis-about-what-you-expect-to-see-every-step-of-the-way-a-manifesto/

Statistical Modeling, Causal Inference, and Social Science 11/13/2024

graphics
Specification curve analysis and the multiverse

https://statmodeling.stat.columbia.edu/2024/11/12/specification-curve-analysis-and-the-multiverse/

Statistical Modeling, Causal Inference, and Social Science 11/12/2024

miscellaneous
Help teaching short-course that has a healthy dose of data simulation

https://statmodeling.stat.columbia.edu/2024/11/11/help-teaching-short-course-that-has-a-healthy-dose-of-data-simulation/

Statistical Modeling, Causal Inference, and Social Science 11/11/2024

bayesian
Meta-analysis with a single study

https://statmodeling.stat.columbia.edu/2024/11/11/meta-analysis-with-a-single-study/

Statistical Modeling, Causal Inference, and Social Science 11/11/2024

bayesian
Prediction markets in 2024 and poll aggregation in 2008

https://statmodeling.stat.columbia.edu/2024/11/10/prediction-markets-in-2024-and-poll-aggregation-in-2008/

Statistical Modeling, Causal Inference, and Social Science 11/10/2024

analysis
Polling by asking people about their neighbors: When does this work? Should people be doing more of it? And the connection to that French dude who bet on Trump

https://statmodeling.stat.columbia.edu/2024/11/09/polling-by-asking-people-about-their-neighbors-when-does-this-work/

Statistical Modeling, Causal Inference, and Social Science 11/09/2024

miscellaneous
If you wanted to be a top tennis player in the late 1930s, there was a huge benefit to being a member of ____. Or to being named ____.

https://statmodeling.stat.columbia.edu/2024/11/08/if-you-wanted-to-be-a-top-tennis-player-in-the-late-1930s-there-was-a-huge-benefit-to-being-a-member-of-____-or-to-being-named-____/

Statistical Modeling, Causal Inference, and Social Science 11/08/2024

sports
Two spans of the bridge of inference

https://statmodeling.stat.columbia.edu/2024/11/08/two-spans-of-the-bridge-of-inference/

Statistical Modeling, Causal Inference, and Social Science 11/08/2024

miscellaneous
Bad science as genre fiction: I think there’s a lot to be said for this analogy!

https://statmodeling.stat.columbia.edu/2024/11/08/bad-science-as-genre-fiction/

Statistical Modeling, Causal Inference, and Social Science 11/08/2024

literature
The Red Sox are hiring

https://statmodeling.stat.columbia.edu/2024/11/07/the-red-sox-are-hiring/

Statistical Modeling, Causal Inference, and Social Science 11/07/2024

sports
Fake data on the honeybee waggle dance, followed by the inevitable “It is important to note that the conclusions of our studies remain firm and sound.”

https://statmodeling.stat.columbia.edu/2024/11/07/fake-data-on-the-honeybee-waggle-dance-followed-by-the-inevitable-it-is-important-to-note-that-the-conclusions-of-our-studies-remain-firm-and-sound/

Statistical Modeling, Causal Inference, and Social Science 11/07/2024

miscellaneous
Reflections on the recent election

https://statmodeling.stat.columbia.edu/2024/11/06/reflections-on-the-recent-election/

Statistical Modeling, Causal Inference, and Social Science 11/06/2024

political
That day in 1977 when Jerzy Neyman committed the methodological attribution fallacy.

https://statmodeling.stat.columbia.edu/2024/11/06/jerzy-neyman-commits-the-methodological-attribution-fallacy/

Statistical Modeling, Causal Inference, and Social Science 11/06/2024

miscellaneous
Self-reference and self-reproduction of evidence

https://statmodeling.stat.columbia.edu/2024/11/05/self-reference-and-self-reproduction-of-evidence/

Statistical Modeling, Causal Inference, and Social Science 11/05/2024

analysis
What if the polls are right? (some scatterplots, and some comparisons to vote swings in past decades)

https://statmodeling.stat.columbia.edu/2024/11/04/what-if-the-polls-are-right-some-scatterplots-and-some-comparisons-to-past-decades/

Statistical Modeling, Causal Inference, and Social Science 11/04/2024

political
Probabilistic numerics and the folk theorem of statistical computing

https://statmodeling.stat.columbia.edu/2024/11/04/probabilistic-numerics-and-the-folk-theorem-of-statistical-computing/

Statistical Modeling, Causal Inference, and Social Science 11/04/2024

bayesian
Interpreting recent Iowa election poll using a rough Bayesian partition of error

https://statmodeling.stat.columbia.edu/2024/11/03/crude-bayesian-updating-from-iowa-election-poll/

Statistical Modeling, Causal Inference, and Social Science 11/03/2024

bayesian
Should pollsters preregister their design, data collection, and analyses?

https://statmodeling.stat.columbia.edu/2024/11/03/should-pollsters-preregister-their-design-data-collection-and-analyses/

Statistical Modeling, Causal Inference, and Social Science 11/03/2024

miscellaneous
Violent science teacher makes ridiculously unsupported research claims, gets treated by legislatures/courts/media as expert on the effects of homeschooling

https://statmodeling.stat.columbia.edu/2024/11/03/violent-science-teacher-makes-ridiculously-unsupported-research-claims-gets-treated-by-legislatures-courts-media-as-expert-on-the-effects-of-homeschooling/

Statistical Modeling, Causal Inference, and Social Science 11/03/2024

causal
A 10% swing in win probability corresponds (approximately) to a 0.4% swing in predicted vote

https://statmodeling.stat.columbia.edu/2024/11/02/a-10-swing-in-win-probability-corresponds-approximately-to-a-0-4-swing-in-predicted-vote/

Statistical Modeling, Causal Inference, and Social Science 11/02/2024

bayesian
Calibration is sometimes sufficient for trusting predictions. What does this tell us when human experts use model predictions?

https://statmodeling.stat.columbia.edu/2024/11/01/calibration-is-sometimes-sufficient-for-trusting-predictions-what-does-this-tell-us-when-human-experts-use-model-predictions/

Statistical Modeling, Causal Inference, and Social Science 11/01/2024

analysis
“Trivia question for you. I kept temperature records for 100 days one year in Boston, starting August 15th (day “0”). What would you guess is the correlation between day# and temp? r=???”

https://statmodeling.stat.columbia.edu/2024/11/01/50749/

Statistical Modeling, Causal Inference, and Social Science 11/01/2024

miscellaneous
Stan Playground: Run Stan on the web, play with your program and data at will, and no need to download anything on your computer

https://statmodeling.stat.columbia.edu/2024/10/31/stan-playground-run-stan-on-the-web-play-with-your-program-and-data-at-will-and-no-need-to-download-anything-on-your-computer/

Statistical Modeling, Causal Inference, and Social Science 10/31/2024

bayesian
StanCon 2024 Oxford: recorded talks are now released!

https://statmodeling.stat.columbia.edu/2024/10/30/stancon-2024-oxford-recorded-talks-are-now-released/

Statistical Modeling, Causal Inference, and Social Science 10/30/2024

bayesian

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