https://hackerpaper.kaipfister.de/p/2011.03567/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMThttps://news.ycombinator.com/item?id=36356377urn:hackerpapers:mention:2011.03567:36356377Fri, 16 Jun 2023 13:37:01 GMT<p>The biggest mistake engineers make is determining sample sizes. It is not trivial to determine the sample size for a trial without prior knowledge of effect sizes. Instead of waiting for a fixed sample size, I would recommend using a sequential testing framework: set a stopping condition and perform a test for each new batch of sample units. This is called optional stopping and it is not possible using a classic t-test, since Type I and II errors are only valid at a determined sample size. However, other tests make it possible: see safe anytime-valid statistics [1, 2] or, simply, bayesian…</p><p><a href="https://hackerpaper.kaipfister.de/p/2011.03567/">Paper and discussion history</a>. A mention is not an endorsement.</p>stat.MEhttps://news.ycombinator.com/item?id=34664614urn:hackerpapers:mention:2011.03567:34664614Sun, 05 Feb 2023 13:06:51 GMT<p>I didn’t see it linked, but a paper by my coworker at Netflix, Michael Lindon, seems relevant: Anytime-Valid Inference for Multinomial Count Data. https://arxiv.org/abs/2011.03567</p><p><a href="https://hackerpaper.kaipfister.de/p/2011.03567/">Paper and discussion history</a>. A mention is not an endorsement.</p>stat.ME