Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Jaudas analīze× | Analīze efektu lielumam× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1969 (1st ed.); 1988 (seminal 2nd ed.) | 1969 (first edition); 1988 (definitive second edition) |
| Autors | Jacob Cohen | Jacob Cohen |
| Tips≠ | Sample size and power planning | Standardized magnitude estimation |
| Pirmavots | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 |
| Citi nosaukumi | sample size calculation, power calculation, sensitivity analysis, a priori power analysis | effect magnitude estimation, standardized effect measure, practical significance analysis, ES analysis |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study. | Effect size analysis quantifies the practical magnitude of a statistical result independently of sample size. Rather than asking only whether a difference or relationship is statistically significant, it asks how large it is, using standardized indices such as Cohen's d, eta-squared, omega-squared, or Pearson's r that allow direct comparison across studies and populations. |
| ScholarGateDatu kopa ↗ |
|
|