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Bayesian Hypothesis Testing Research
Bayesian hypothesis testing research is a quantitative design in which competing hypotheses are evaluated by updating prior beliefs with observed data to produce posterior probabilities and Bayes factors. Unlike frequentist null-hypothesis significance testing, it quantifies the relative evidence for each hypothesis, supports optional stopping, and allows accumulation of evidence across studies without inflating Type I error rates.
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Sources
- Jeffreys, H. (1961). Theory of Probability (3rd ed.). Oxford University Press. ISBN: 978-0198503682
- Wagenmakers, E.-J. (2010). A practical solution to the pervasive problems of p values. Psychonomic Bulletin and Review, 14(5), 779–804. DOI: 10.3758/BF03194105 ↗