#HypothesisTesting
Live, measured metrics for the hashtag #HypothesisTesting from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #hypothesistesting
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Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-07-27 11:17 UTC0 uses by 0 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-07-27 11:17 UTCNo related tags with measured usage found for #hypothesistesting.
Live pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-07-27 11:17 UTCEverything below is measured over the latest 20 public posts (spanning ~31019 hours).
Posting hours (UTC) — busiest: 11:00
Languages: English (20)
Avg boosts / post: 1.4
Top of the latest posts
#statstab #478 Equivalence Tests {marginaleffects} Thoughts: Often you want to test "no difference" in more complex models than many packages or software permit. With a few lines of code you can do that for most models. #Equivalence #noeffe
Part II of my series on what to do with non-significant results is up now. In this post, I focus on how to determine if your data is compatible with the claim of "no effect" (and why relying on p-values is wrong). It covers TOST equivalence
How I Built a Company That Got Featured in Business Week #Entrepreneurship Link: https://www.youtube.com/shorts/ig4hKL3BLBE #DataScience #AppliedStatistics #HypothesisTesting #DataDrift #PythonStatistics
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/hypothesistesting