Bayesian Confidence Intervals
Bayesian Confidence Intervals is a statistical interval estimation method that quantifies the uncertainty of a parameter by specifying a range of values within which the parameter lies with a certain probability, derived from the posterior distribution in a Bayesian framework, thereby distinguishing it from frequentist confidence intervals by incorporating prior knowledge and yielding direct probabilistic interpretations about the parameter.
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535
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Publications per year
2017–2026
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The Insignificance of Statistical Significance Testing
Douglas H. Johnson · Journal of Wildlife Management · 1999 · 1.1K citations
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King Mongkut's University of Technology North Bangkok, Thailand
12 publications · 282 citations
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King Mongkut's University of Technology North Bangkok, Thailand
11 publications · 261 citations
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King Mongkut's University of Technology North Bangkok, Thailand
6 publications · 161 citations
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King Mongkut's University of Technology North Bangkok
Bangkok, Thailand
13 h-index
46 publications
1.2K citations
Stanford University
Stanford, United States
10 h-index
11 publications
474 citations

Centre National de la Recherche Scientifique
Paris, France
9 h-index
18 publications
552 citations

Al-Azhar University
Cairo, Egypt
7 h-index
8 publications
136 citations
University of Michigan
Ann Arbor, United States
7 h-index
12 publications
425 citations
University College London
London, United Kingdom
7 h-index
9 publications
927 citations

King Abdulaziz University
Jeddah, Saudi Arabia
7 h-index
9 publications
22.4K citations
University of Florida
Gainesville, United States
6 h-index
11 publications
402 citations
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18 publications · 2.3K citations
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21 publications · 1.3K citations
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JSCS · 12 publications · 393 citations
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11 publications · 484 citations
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