Miha Gazvoda
@mihagazvoda.bsky.social
data scientist @ http://booking.com | blog @ http://mihagazvoda.com | outdoor sports | priors my own
Reposted by Miha Gazvoda
If your frequentist analysis gives the same result as a Bayesian analysis, that means nothing for either paradigm. No frequentist is bothered that Bayes "works" - they use Bayesian calculations all the time. No Bayesian is bothered that a freq estimator agrees - it's interpretation that is doubted.
June 4, 2025 at 6:30 AM
If your frequentist analysis gives the same result as a Bayesian analysis, that means nothing for either paradigm. No frequentist is bothered that Bayes "works" - they use Bayesian calculations all the time. No Bayesian is bothered that a freq estimator agrees - it's interpretation that is doubted.
I’ve written a personal-view article, “A Reality Check on Null Hypothesis Significance Testing in A/B Testing", soon appearing in Eppo’s Outperform magazine (print).
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May 6, 2025 at 7:40 PM
I’ve written a personal-view article, “A Reality Check on Null Hypothesis Significance Testing in A/B Testing", soon appearing in Eppo’s Outperform magazine (print).
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Reposted by Miha Gazvoda
November 11, 2024 at 2:57 PM
Reposted by Miha Gazvoda
Since it is inefficient to attempt to educate every reviewer individually, I am yeeting into your feed this clear paper from Gelman, Hill, and Yajima on how Bayesians can do even better than correcting for multiple comparisons. arxiv.org/abs/0907.2478
Why we (usually) don't have to worry about multiple comparisons
Applied researchers often find themselves making statistical inferences in settings that would seem to require multiple comparisons adjustments. We challenge the Type I error paradigm that underlies t...
arxiv.org
November 26, 2024 at 9:11 AM
Since it is inefficient to attempt to educate every reviewer individually, I am yeeting into your feed this clear paper from Gelman, Hill, and Yajima on how Bayesians can do even better than correcting for multiple comparisons. arxiv.org/abs/0907.2478