{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreidf75ef6bokk4drxr3ihg2frmdyovkewxypk34ushm5sxzucgso6y",
    "uri": "at://did:plc:wwyqal4cnqhuwyacdj7rqq3n/app.bsky.feed.post/3mevrb5x4dix2"
  },
  "path": "/t/significance-versus-hypothesis-testing/28638#post_7",
  "publishedAt": "2026-02-15T08:54:28.000Z",
  "site": "https://discourse.datamethods.org",
  "textContent": "ChristopherTong:\n\n> Also how do you propose we plan a study without NP-influenced ideas such as power analysis or precision analysis?\n\nI think sample-size calculations are over-rated. We should probably abandon them for observational studies and for experimental studies I do not really see how knowledge of the predicted long run proportion of rejected tested hypotheses given a fixed type I and II error really helps anyone or even the researcher. Perhaps, we should be pragmatic about such trials e.g. what sample size is required for the range of tested hypotheses under which the data would not be considered unusual to be no more than ±10%?.",
  "title": "Significance versus hypothesis testing"
}