Porównaj metody
Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Analiza mocy dla testów proporcji× | Test niezależności chi-kwadrat× | |
|---|---|---|
| Dziedzina | Statystyka | Statystyka |
| Rodzina | Hypothesis test | Hypothesis test |
| Rok powstania≠ | 1988 | 1900 |
| Twórca≠ | Jacob Cohen | Karl Pearson |
| Typ≠ | Sample size determination | Nonparametric test of association |
| Źródło pierwotne≠ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. DOI ↗ | Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175. DOI ↗ |
| Inne nazwy | proportion power analysis, two-proportion z-test power, z-test for proportions power, Oran Testi Güç Analizi | chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi |
| Pokrewne≠ | 3 | 2 |
| Podsumowanie≠ | Power analysis for proportion tests is a prospective sample-size planning method used to determine how many participants are needed to detect a meaningful difference between two (or one) proportions with a specified probability. Formalised by Jacob Cohen in his 1988 landmark text, it applies the arcsine transformation to convert proportions into the effect-size index h, enabling direct calculation of the required sample size. | The chi-square test of independence is a nonparametric hypothesis test that examines whether two categorical variables are associated by comparing observed and expected frequencies in a cross-tabulation. It rests on the chi-square criterion introduced by Karl Pearson in 1900. |
| ScholarGateZbiór danych ↗ |
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