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المجالتصميم البحثتصميم البحث
العائلةProcess / pipelineProcess / pipeline
سنة النشأة1935–1961 (Jeffreys); extended by Kass & Raftery 1995, Wagenmakers 2007–2010Early 20th century (Fisher 1925; Neyman–Pearson 1933)
صاحب الطريقةHarold Jeffreys (formal Bayes factor framework)Karl Pearson, Ronald A. Fisher, Jerzy Neyman, Egon Pearson
النوعQuantitative research designQuantitative confirmatory research design
المصدر التأسيسيJeffreys, H. (1961). Theory of Probability (3rd ed.). Oxford University Press. ISBN: 978-0198503682Kerlinger, F. N., & Lee, H. B. (1986). Foundations of Behavioral Research (3rd ed.). Holt, Rinehart and Winston. ISBN: 978-0030417603
الأسماء البديلةBayesian significance testing, Bayes factor hypothesis testing, BHT research, Bayesian inference testinghypothetico-deductive research, confirmatory quantitative research, null hypothesis significance testing, NHST design
ذات صلة54
الملخصBayesian 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.Hypothesis testing research is a quantitative design in which the investigator derives one or more explicit, falsifiable propositions from theory, translates them into a null hypothesis (H0) and an alternative hypothesis (H1), collects empirical data, and then applies an inferential statistical test to decide whether the evidence is sufficient to reject H0. The approach is the dominant paradigm for confirmatory science across the social, behavioral, health, and natural sciences.
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ScholarGateقارن الطرق: Bayesian Hypothesis Testing Research · Hypothesis Testing Research. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare