So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Phân tích cỡ mẫu mạnh mẽ× | Thống kê mô tả mạnh mẽ× | |
|---|---|---|
| Lĩnh vực | Thống kê | Thống kê |
| Họ | Hypothesis test | Hypothesis test |
| Năm ra đời≠ | 2005 (formalized) | 1960s–1970s |
| Người khởi xướng≠ | Algina, Keselman & Penfield; Wilcox | John W. Tukey, Peter J. Huber, Frank Hampel |
| Loại≠ | Robust effect size estimation | Resistant summary measures |
| Công trình gốc≠ | Algina, J., Keselman, H. J., & Penfield, R. D. (2005). An alternative to Cohen's standardized mean difference effect size: A robust parameter and confidence interval in the two independent groups case. Psychological Methods, 10(3), 317–328. DOI ↗ | Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165 |
| Tên gọi khác | robust Cohen's d, trimmed-mean effect size, outlier-resistant effect size, robust standardized mean difference | resistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | Robust effect size analysis quantifies the magnitude of a difference or association using estimators that are resistant to outliers and violations of normality. Rather than relying on classical statistics such as Cohen's d based on sample means and standard deviations, robust variants use trimmed means and Winsorized standard deviations to produce effect size estimates that accurately reflect the typical effect rather than being inflated by extreme values. | Robust descriptive statistics summarize the location, spread, and shape of a dataset using measures that remain meaningful even when a fraction of the data contains outliers or severe departures from normality. Core tools include the median, trimmed mean, interquartile range (IQR), and median absolute deviation (MAD), all of which are resistant to contamination that would distort the classic mean and standard deviation. |
| ScholarGateBộ dữ liệu ↗ |
|
|