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| Analisis Kuasa Statistik untuk Korelasi Pearson× | Korelasi Momem Hasil Pearson× | |
|---|---|---|
| Bidang | Statistik | Statistik |
| Keluarga | Hypothesis test | Hypothesis test |
| Tahun asal≠ | 1988 | 1895 |
| Pengasas≠ | Jacob Cohen | Karl Pearson |
| Jenis≠ | Sample size / power determination | Parametric correlation |
| Sumber perintis | 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. DOI ↗ |
| Alias≠ | Korelasyon Güç Analizi, power analysis for r, sample size for correlation | pearson r, product-moment correlation, bivariate correlation, Pearson Korelasyon Analizi |
| Berkaitan | 4 | 4 |
| Ringkasan≠ | 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. | The Pearson product-moment correlation coefficient (r) is a parametric measure of the direction and strength of the linear association between two continuous variables. Introduced by Karl Pearson in 1895, it remains the most widely used bivariate correlation statistic in the social, health, and natural sciences. The coefficient ranges from −1 (perfect negative linear relationship) to +1 (perfect positive), with 0 indicating no linear association. |
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