What is recorded here?
Neyman and Pearson organized statistical tests around error rates and power, deriving most-powerful tests for specified hypothesis comparisons.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The optimality result requires its stated hypotheses and constraints. A significance test does not give the probability that a scientific theory is true, and statistical support does not replace replication.
Read the original work
- IX. On the problem of the most efficient tests of statistical hypotheses
- IX. On the problem of the most efficient tests of statistical hypotheses — deposited bibliography
- Original Neyman–Pearson paper
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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People and systems
Jerzy Neyman; Egon Sharpe Pearson
Source paper byline retained, including repeated label positions. Names are not verified unique identities or measurements of individual effort.
Research locations and affiliations
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Documented countries / regions: Poland, United Kingdom
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English catalogue narrative
Neyman–Pearson hypothesis testing
Neyman and Pearson organized statistical tests around error rates and power, deriving most-powerful tests for specified hypothesis comparisons.
Scientific scope
The optimality result requires its stated hypotheses and constraints. A significance test does not give the probability that a scientific theory is true, and statistical support does not replace replication.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Jerzy Neyman; Egon Sharpe Pearson
Source paper byline retained, including repeated label positions. Names are not verified unique identities or measurements of individual effort.