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| Phân tích sức mạnh thống kê cho Tương quan Pearson× | Hệ số tương quan hạng Spearman× | |
|---|---|---|
| Lĩnh vực | Thống kê | Thống kê |
| Họ | Hypothesis test | Hypothesis test |
| Năm ra đời≠ | 1988 | 1904 |
| Người khởi xướng≠ | Jacob Cohen | Charles Spearman |
| Loại≠ | Sample size / power determination | Nonparametric rank-based correlation |
| Công trình gốc≠ | Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832 | Spearman, C. (1904). The proof and measurement of association between two things. The American Journal of Psychology, 15, 72–101. DOI ↗ |
| Tên gọi khác | Korelasyon Güç Analizi, power analysis for r, sample size for correlation | Spearman's rho, Spearman rank-order correlation, Spearman Sıra Korelasyonu |
| Liên quan | 4 | 4 |
| Tóm tắt≠ | 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 Spearman rank correlation coefficient (ρ) is a nonparametric measure of the monotonic association between two variables. Introduced by Charles Spearman in 1904, it converts raw observations to ranks and measures how consistently one variable increases as the other increases, without assuming a normal distribution or a linear relationship. |
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