Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| ANOVA ya Kibayesi× | Markov Chain Monte Carlo (MCMC)× | Uchanganuzi wa Faulo wa Njia Moja× | |
|---|---|---|---|
| Nyanja≠ | Mbinu za Bayes | Mbinu za Bayes | Takwimu |
| Familia≠ | Bayesian methods | Bayesian methods | Hypothesis test |
| Mwaka wa asili≠ | 2012 | — | 1925 |
| Mwanzilishi≠ | Rouder, Morey, Speckman & Province | — | Ronald A. Fisher |
| Aina≠ | Bayesian hypothesis test / group comparison | Posterior sampling algorithm | Parametric mean comparison |
| Chanzo asilia≠ | 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 | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| Majina mbadala≠ | bayesian analysis of variance, bayes factor ANOVA, JZS ANOVA, Bayesçi ANOVA — Bayes Faktörü ile Grup Karşılaştırması | markov chain monte carlo, MCMC sampling, MCMC (Markov Zinciri Monte Carlo) | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| Zinazohusiana≠ | 4 | 3 | 4 |
| Muhtasari≠ | 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. | Markov Chain Monte Carlo (MCMC) is a family of computational algorithms for sampling from complex probability distributions, most commonly the posterior distributions that arise in Bayesian inference. Rather than computing posteriors analytically — which is rarely possible for realistic models — MCMC constructs a Markov chain whose stationary distribution is the target posterior and draws dependent samples from it, enabling full probabilistic inference for virtually any model. | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. |
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