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| ANOVA Bayesiana× | Regressione Bayesiana× | |
|---|---|---|
| Campo | Bayesiano | Bayesiano |
| Famiglia | Bayesian methods | Bayesian methods |
| Anno di origine≠ | 2012 | — |
| Ideatore≠ | Rouder, Morey, Speckman & Province | — |
| Tipo≠ | Bayesian hypothesis test / group comparison | Bayesian linear model |
| Fonte seminale≠ | Rouder, J. N., Morey, R. D., Speckman, P. L. & Province, J. M. (2012). Default Bayes Factors for ANOVA Designs. Journal of Mathematical Psychology, 56(5), 356–374. DOI ↗ | Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955 |
| Alias≠ | bayesian analysis of variance, bayes factor ANOVA, JZS ANOVA, Bayesçi ANOVA — Bayes Faktörü ile Grup Karşılaştırması | bayesian linear regression, probabilistic regression, bayesian regresyon |
| Correlati≠ | 4 | 2 |
| Sintesi≠ | Bayesian ANOVA, formalised by Rouder, Morey, Speckman and Province (2012), tests whether group means differ by quantifying the evidence for the alternative hypothesis relative to the null using the Bayes Factor (BF₁₀). Unlike classical ANOVA, it can also measure evidence in favour of the null hypothesis, making it equally informative when groups do not differ. | Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off. |
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