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| Anàlisi de potència del Chi-quadrat× | Anàlisi de potència estadística per a la correlació de Pearson× | |
|---|---|---|
| Camp | Estadística | Estadística |
| Família | Hypothesis test | Hypothesis test |
| Any d'origen | 1988 | 1988 |
| Autor original | Jacob Cohen | Jacob Cohen |
| Tipus≠ | Sample size and power calculation | Sample size / power determination |
| Font seminal | 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 |
| Àlies≠ | 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 |
| Relacionats≠ | 2 | 4 |
| Resum≠ | 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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