Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Робастные описательные статистики× | Робастный t-критерий для независимых выборок× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Hypothesis test | Hypothesis test |
| Год появления≠ | 1960s–1970s | 1974–1990s |
| Автор метода≠ | John W. Tukey, Peter J. Huber, Frank Hampel | Rand R. Wilcox; Karen K. Yuen (trimmed-mean form) |
| Тип≠ | Resistant summary measures | Robust parametric mean comparison |
| Основополагающий источник≠ | Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165 | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 |
| Другие названия | resistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation | Yuen's t-test, trimmed-mean t-test, Winsorized t-test, robust two-sample test |
| Связанные≠ | 5 | 2 |
| Сводка≠ | 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. | The robust independent samples t-test compares the central tendency of two independent groups using trimmed means and Winsorized variances, making it substantially less sensitive to outliers and non-normality than the classical Student or Welch t-test. The most widely used form is Yuen's test, which also accommodates unequal variances across groups. |
| ScholarGateНабор данных ↗ |
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