Confirming Statistical Hypotheses is a research paper published in Journal of the Royal Statistical Society Series B: Statistical Methodology (1957). On theSindex it has a DataRank of 0.522. It has been cited 4 times, with 4 citing works in its 1-hop citation network.
Summary This paper distinguishes between the acceptability and the confirmation of a statistical hypothesis. A hypothesis is called acceptable if it is accepted by a significance test or some similar procedure and unacceptable if it is rejected. The likelihood ratio criterion of acceptability is discussed. In order to define confirmation, a distance function is introduced in the hypothesis space which reflects the size of the departure of any hypothesis from the null hypothesis. All admissible hypotheses are tested and classified as acceptable or unacceptable. If none of the acceptable hypotheses are “near” the null hypothesis, the latter is disconfirmed; if all the acceptable hypotheses are “near” the null hypothesis, it is confirmed; otherwise the experiment is inconclusive and the null hypothesis is unconfirmed. In the second part of the paper these ideas are applied to some common statistical techniques.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.241
From this paper's citation signal
Citation Network Contribution
0.280
From 4 citing papers with measurable signal
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 46% comes from its base citations and 54% from the citation network (4 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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