please ignore everything i have said or done in the past
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The sample-ratio-mismatch in AB testing.
Source: https://www.linkedin.com/posts/ronnyk_experimentguide-abtests-activity-6954129174039068672-pLwN
Looking at segments in A/B tests, or controlled experiments, is very useful, but there are dangerous pitfalls. It is possible to improve c
Reply-Reply to Purified-Zone: A/B See?
purified-zone replied to your post “eightyonekilograms: Inspired by a recent post, which the user asked...”
wtf is ab damn wikipedia aint helpin shit
It’s split-testing. Here’s The Wikipage. Wiki can tend towards the jargonistic, so to explain: it’s just taking two slightly different versions of Something, and showing them to an audience sample to see which one is liked better by your audience. Like op says: this is great for telling you which is liked better but, unless you take steps to counter it, it doesnt tell you anything about the Amplitude of the like/dislike.
We Use a Simple Example to Explore the Ins and Outs of A/B Testing (a.k.a. Hypothesis Testing)
HT @DataSciNews #datascience
to the tune of Hallelujah by Leonard Cohen: somebody once told me the world is gonna roll me, i ain't the sharpest tool in the shed

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talking to my therapist: please ignore everything i have said in the past
https://twitter.com/gershbrain/status/1250467765632348162?s=21
Good reads on A/B testing
The math behind A/B testing: https://web.archive.org/web/20150921174256/https:/developer.amazon.com/public/apis/manage/ab-testing/doc/math-behind-ab-testing
Data science you need to know: A/B testing. https://michael-bar.github.io/Introduction-to-statistics/AMP-2-RCT-principles.html
5 things to know about A/B testing: https://www.kdnuggets.com/2018/09/5-things-know-about-ab-testing.html
Optimizely’s introduction on A/B testing: https://www.optimizely.com/optimization-glossary/ab-testing/
How now to run A/B tests: https://www.evanmiller.org/how-not-to-run-an-ab-test.html
Guidelines for A/B testing: https://hookedondata.org/guidelines-for-ab-testing/