13.16 Meeting Videos
13.16.2 Cohort 2
Meeting chat log
00:11:46 Ricardo Serrano: Frequentists vs Bayesian Statistics https://towardsdatascience.com/frequentist-vs-bayesian-statistics-54a197db21Meeting chat log
00:21:28 Ricardo Serrano: Julia Silge blog episode use of tidymodels 'infer' package for statistical inference https://juliasilge.com/blog/tuskegee-airmen/
01:08:00 Federica Gazzelloni: resources from the course: https://rafalab.github.io/pages/harvardx.html13.16.3 Cohort 3
Meeting chat log
00:07:53 Mei Ling Soh: https://github.com/sohmeiling/islr_chapter13_multiple-testing
00:09:19 Mei Ling Soh: https://github.com/sohmeiling/islr_chapter13_multiple-testing
00:39:43 Fariborz Soroush: Sorry IT pushed an update on my system :|
00:39:54 Fariborz Soroush: I just joinedMeeting chat log
00:45:34 Mei Ling Soh: https://rpubs.com/Mei_Ling/938384
00:45:35 Mei Ling Soh: https://r4ds.github.io/bookclub-islr/a-re-sampling-approach.html
00:45:54 Mei Ling Soh: https://github.com/sohmeiling/islr_chapter13_multiple-testing13.16.4 Cohort 4
Meeting chat log
00:53:00 Ron: FROM "Regression and Other Stories":
The three challenges of statistical inference are:
1. Generalizing from sample to population, a problem that is associated with survey sampling but
actually arises in nearly every application of statistical inference;
2. Generalizing from treatment to control group, a problem that is associated with causal inference,
which is implicitly or explicitly part of the interpretation of most regressions we have seen; and
3. Generalizing from observed measurements to the underlying constructs of interest, as most of the
time our data do not record exactly what we would ideally like to study.
01:00:11 Ron: Might be of interest, Gelman on multiple comparisons in Bayesian methods : http://www.stat.columbia.edu/~gelman/research/published/multiple2f.pdf
01:03:45 kevin_kent: https://linear.axler.net/
01:06:14 Ron: "Down with determinants" lol