Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Chi-ruudu võimsusanalüüs× | Statistiline jäävushinnangu analüüs Pearsoni korrelatsiooni jaoks× | |
|---|---|---|
| Valdkond | Statistika | Statistika |
| Perekond | Hypothesis test | Hypothesis test |
| Tekkeaasta | 1988 | 1988 |
| Looja | Jacob Cohen | Jacob Cohen |
| Tüüp≠ | Sample size and power calculation | Sample size / power determination |
| Algallikas | 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 |
| Rööpnimetused≠ | chi-square power, chi-square sample size, Ki-Kare Güç Analizi, goodness-of-fit power | Korelasyon Güç Analizi, power analysis for r, sample size for correlation |
| Seotud≠ | 2 | 4 |
| Kokkuvõte≠ | Chi-square power analysis is a prospective calculation that determines the minimum sample size required — or the statistical power achievable with a given sample — for chi-square independence tests or goodness-of-fit tests. It rests on Cohen's w effect size framework, codified by Jacob Cohen in his landmark 1988 work on statistical power for the behavioral sciences. | Correlation power analysis is a pre-study calculation that determines how many participants are needed — or how much statistical power an existing sample provides — for a Pearson correlation test. Formalised by Jacob Cohen in his landmark 1988 text, it uses the expected correlation coefficient r directly as the effect size, so researchers can plan studies that are neither underpowered nor wastefully large. |
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