Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Bajesieša t-tests× | Neatkarīgo paraugu t-tests× | |
|---|---|---|
| Nozare≠ | Bajesa metodes | Statistika |
| Saime≠ | Bayesian methods | Hypothesis test |
| Izcelsmes gads≠ | 2009 | 1908 |
| Autors≠ | Rouder, Speckman, Sun, Morey & Iverson | Student (W. S. Gosset) |
| Tips≠ | Bayesian hypothesis test | Parametric mean comparison |
| Pirmavots≠ | Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D. & Iverson, G. (2009). Bayesian t Tests for Accepting and Rejecting the Null Hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237. DOI ↗ | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ |
| Citi nosaukumi≠ | bayesian two-sample t-test, bayes factor t-test, Bayesçi t-Testi | student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | The Bayesian t-test, formalised by Rouder and colleagues in 2009, is a two-group comparison method that works within a Bayesian framework. Instead of a p-value, it produces a Bayes Factor (BF₁₀) that quantifies the evidence the data provide for the alternative hypothesis relative to the null, and it reports the full posterior distribution of the standardised effect size δ with a highest-density interval. | The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances. |
| ScholarGateDatu kopa ↗ |
|
|