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P-Value and Statistical Significance/证据
方法证据记录

P-Value and Statistical Significance

The p-value is the probability of observing data as extreme as or more extreme than what was actually observed, assuming the null hypothesis is true. Introduced by Ronald Fisher in 1925, it is the foundation of frequentist hypothesis testing. Statistical significance is declared when the p-value falls below a pre-specified threshold (alpha level, typically 0.05).

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源记录

引文逐字复制自方法源记录。这些引文不代表任何层级的验证。

P-Value and the Concept of Statistical Significance in Hypothesis Testing
分类方法记录 · process-pipeline / research-statistics
  • Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd. · URL
  • Neyman, J., & Pearson, E. S. (1933). On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society, 231, 289–337. · DOI 10.1098/rsta.1933.0009
  • Wasserstein, R. L., & Lazar, N. A. (2016). The ASA Statement on p-Values: Context, Process, and Purpose. The American Statistician, 70(2), 129–133. · DOI 10.1080/00031305.2016.1154108
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Same method familyEffect Sizemachine-suggested · Relational suggestion, not evidence.Same method familyMultiple Comparisons Problemmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketNull Hypothesis Testingmachine-suggested · Relational suggestion, not evidence.Same method familyStatistical Power and Sample Sizemachine-suggested · Relational suggestion, not evidence.Same method familyType I and Type II Errorsmachine-suggested · Relational suggestion, not evidence.

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Bibliographic sources are present. Claim-level evidence review has not been performed.

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