Porównaj metody
Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Analiza wielkości efektu× | Analiza mocy× | |
|---|---|---|
| Dziedzina | Statystyka | Statystyka |
| Rodzina | Hypothesis test | Hypothesis test |
| Rok powstania≠ | 1969 (first edition); 1988 (definitive second edition) | 1969 (1st ed.); 1988 (seminal 2nd ed.) |
| Twórca | Jacob Cohen | Jacob Cohen |
| Typ≠ | Standardized magnitude estimation | Sample size and power planning |
| Źródło pierwotne | 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 |
| Inne nazwy | effect magnitude estimation, standardized effect measure, practical significance analysis, ES analysis | sample size calculation, power calculation, sensitivity analysis, a priori power analysis |
| Pokrewne≠ | 4 | 5 |
| Podsumowanie≠ | 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. | 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. |
| ScholarGateZbiór danych ↗ |
|
|