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the claim

A p-value is the probability of obtaining results at least as extreme as those observed, assuming the null hypothesis is true.

the verdict
SUPPORTED
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Recorded sources
8 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that a p-value is the probability of obtaining results at least as extreme as those observed, assuming the null hypothesis is true?

Yes. Multiple peer-reviewed sources and a reference work state the standard definition: the p-value is the probability of obtaining results at least as extreme as those observed, assuming the null hypothesis is true. One source notes this is the conventional interpretation while discussing alternative framings.

Verdict: SUPPORTED · 8 sources for, 0 against · Last checked

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Evidence for · 8
2024
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Carazo-Díaz, C. & Prieto-Valiente, L. (2024). The p-value of a test is not the probability that the null hypothesis is true or false. doi.org. https://doi.org/10.33588/rn.7910.2024318

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More for · 7
2025
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Nicolao, G., Fordellone, M., Schiattarella, P., Smimmo, A., Gennaro, P. D., & Speranza, T. (2025). Decision Rules in Frequentist and Bayesian Hypothesis Testing: P-Value and Bayes Factor. doi.org. https://doi.org/10.54103/2282-0930/29432

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p-value - Wikipedia. (n.d.). en.wikipedia.org. https://en.wikipedia.org/wiki/P-value

2016
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Hazra, A. & Gogtay, N. (2016). Biostatistics series module 2: Overview of hypothesis testing. doi.org. https://doi.org/10.4103/0019-5154.177775

2020
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Significance of p value in postgraduate thesis: do we need to change anything?. (2020). doi.org. https://doi.org/10.1136/postgradmedj-2019-137439

2025
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The false evidence rate: An approach to frequentist error rate control conditioning on the observed P value. (2025). doi.org. https://doi.org/10.1073/pnas.2415706122

2018
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Why a P-Value is Not Enough. (2018). doi.org. https://doi.org/10.1097/bsd.0000000000000695

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The Probability that Your Hypothesis Is Correct, Credible Intervals, and Effect Sizes for IR Evaluation. (n.d.). cir.nii.ac.jp. https://doi.org/10.1145/3077136.3080766

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