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| Uchanganuzi wa Kiwango cha Uwezekano wa Uhalifu (LR)× | Bayes Factor Test× | |
|---|---|---|
| Nyanja≠ | Sayansi ya Forensiki | Mbinu za Bayes |
| Familia≠ | Regression model | Bayesian methods |
| Mwaka wa asili≠ | 2004 | 1961 |
| Mwanzilishi≠ | Colin Aitken & Franco Taroni | Harold Jeffreys |
| Aina≠ | Bayesian evidence evaluation model | Bayesian hypothesis comparison |
| Chanzo asilia≠ | Aitken, C. G. G., & Taroni, F. (2004). Statistics and the Evaluation of Evidence for Forensic Scientists (2nd ed.). Wiley. ISBN: 978-0-470-84367-3 | Jeffreys, H. (1961). Theory of Probability (3rd ed.). Clarendon Press / Oxford University Press. ISBN: 978-0198503682 |
| Majina mbadala | Bayes Factor in Forensics, Forensic Evidence Weight, LR-Based Forensic Evaluation, Adli Olabilirlik Oranı | bayes factor, BF10, Bayesian hypothesis test, Bayes Faktörü — Hipotez Testi |
| Zinazohusiana | 3 | 3 |
| Muhtasari≠ | The Forensic Likelihood Ratio (LR) is a Bayesian framework for quantifying the weight of forensic evidence relative to two competing propositions — typically the prosecution and defence hypotheses. Formally developed and systematised by Colin Aitken and Franco Taroni in their 2004 Wiley monograph, the LR expresses how much more probable the observed evidence is under one hypothesis than under the other, providing the court with a single, interpretable number that separates the scientist's role from the fact-finder's role. | The Bayes factor test, formalised by Harold Jeffreys in 1961, is a Bayesian method for comparing two competing hypotheses. Rather than returning a binary reject/retain verdict, it produces a continuous ratio BF₁₀ that quantifies how much more (or less) probable the data are under the alternative hypothesis H₁ than under the null hypothesis H₀. |
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