Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Jaudas analīze t-testam× | Neatkarīgo paraugu t-tests× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1969 | 1908 |
| Autors≠ | Jacob Cohen | Student (W. S. Gosset) |
| Tips≠ | Sample size determination | Parametric mean comparison |
| Pirmavots≠ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ |
| Citi nosaukumi≠ | t-test power analysis, sample size calculation for t-test, Güç Analizi — t-Testi | student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | Power analysis for the t-test is a sample size planning procedure that determines how many participants are required to detect a mean difference of a given magnitude with acceptable probability. Formalised by Jacob Cohen in his 1969 and 1988 editions of Statistical Power Analysis for the Behavioral Sciences, it links four quantities — effect size (Cohen's d), significance level (α), statistical power (1 − β), and sample size — so that fixing any three allows calculation of the fourth. | 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. |
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