90% of the T Distribution
William Sealy Gosset, known as Student, developed the t distribution to improve statistical analysis, particularly in estimating confidence intervals. He introduced correction factors to account for uncertainty in standard deviation estimation, which are crucial for accurate confidence intervals. This article discusses how to apply these corrections and provides practical examples of their use in statistical evaluations.
- ▪William Sealy Gosset invented the t distribution to enhance statistical methods.
- ▪He created correction tables for confidence intervals based on sample size.
- ▪The article explains how to calculate confidence intervals using correction factors.
Hacker News (Newest) files mainly under programming. We currently carry 5,306 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
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 | Entropicthoughts |
| Canonical URL | https://entropicthoughts.com/ninety-percent-of-the-t-distribution |
| Publication time | Wed, 27 May 2026 13:29:40 +0000 |
| Retrieval time | 2026-05-27T13:38:00.837Z |
| Last seen | 2026-05-27T13:38:00.837Z |
| 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 | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| 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
90 % of the t distribution by kqr, scheduled 2026-05-26 Tags: forecasting statistics William Sealy Gosset was great. He improved beer at Guinness by using the statistics that existed at the time. Not happy with that, he invented new statistics to brew even better beer. The things he invented are used all over the place now, but Guinness wanted to keep him a secret weapon, so they made him publish his results under the fake name Student. One thing Gosset realised is that it is wrong to compute 90 % confidence intervals for the mean by taking the standard deviation of the sample, and assume a normal distribution, like-a-so: \[\hat{\mu} \pm 1.645 \hat{\sigma}\] When we do this we get too narrow a range, because while we recognise \(\hat{\mu}\) is just an approximation, we are assuming we…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Entropicthoughts.
Discussion
0 commentsMore from Entropicthoughts
