Stop Calling the First Significant Day a Win
Product Management Stop Calling the First Significant Day a Win Checking an A/B test until it crosses p < 0.05 can turn a nominal 5 percent false-positive rate into almost 28 percent. I use a seeded simulation to show how large the damage gets and compare the fixes that keep early stopping honest. Mila Sudarikova Aug 11, 2026 12 min read Share Most teams treat A/B testing in a fairly straightforward way.
- ▪Product Management Stop Calling the First Significant Day a Win Checking an A/B test until it crosses p < 0.05 can turn a nominal 5 percent false-positive rate into almost 28 percent.
- ▪I use a seeded simulation to show how large the damage gets and compare the fixes that keep early stopping honest.
- ▪Mila Sudarikova Aug 11, 2026 12 min read Share Most teams treat A/B testing in a fairly straightforward way.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Towards Data Science |
| Canonical URL | https://towardsdatascience.com/stop-calling-the-first-significant-day-a-win/ |
| Publication time | Tue, 11 Aug 2026 16:30:00 +0000 |
| Retrieval time | 2026-08-11T16:35:42.342Z |
| Last seen | 2026-08-11T16:35:42.342Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | ayZi8trT2rwd · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Product Management Stop Calling the First Significant Day a Win Checking an A/B test until it crosses p < 0.05 can turn a nominal 5 percent false-positive rate into almost 28 percent. I use a seeded simulation to show how large the damage gets and compare the fixes that keep early stopping honest. Mila Sudarikova Aug 11, 2026 12 min read Share Most teams treat A/B testing in a fairly straightforward way. They launch a test, open the dashboard every morning, and wait for the p-value to drop below 0.05. When it does, the result looks official enough to ship. The line has been crossed, the number looks clean, and the winner seems ready to call. I would not say that this routine is always done carelessly.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
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