Two-sided Tests
Two-Sided Tests is a statistical hypothesis testing framework that belongs to the class of inferential methods designed to evaluate the extremity of a test statistic in both directions relative to the null distribution, distinguishing itself by assessing deviations from the null hypothesis in either tail of the distribution rather than in a single specified direction.
383
Publications
24K
Citations
645
Authors
341
Institutions
Publications per year
2017–2026
33
Variants
Two-tailed Hypothesis TestsTwo-tailed Tests
Parents
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1–5 of 383
645
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341
University of Florida
Gainesville, United States
8 h-index
11 publications
588 citations

McMaster University
Hamilton, Canada
7 h-index
8 publications
615 citations

Universidad de Granada
Granada, Spain
5 h-index
7 publications
124 citations
Harvard University
Cambridge, United States
5 h-index
10 publications
667 citations
University of Pennsylvania
Philadelphia, United States
5 h-index
7 publications
426 citations
Iowa State University
Ames, United States
5 h-index
7 publications
1.1K citations
Technion – Israel Institute of Technology
Haifa, Israel
5 h-index
7 publications
156 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
4 h-index
8 publications
171 citations
1–8 of 341
38 publications · 2.9K citations
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25 publications · 1.5K citations
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19 publications · 831 citations
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17 publications · 1.6K citations
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12 publications · 1.4K citations
12
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