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| Robustā aprakstošā statistika× | Robustā neatkarīgo paraugu t-kriterijs× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1960s–1970s | 1974–1990s |
| Autors≠ | John W. Tukey, Peter J. Huber, Frank Hampel | Rand R. Wilcox; Karen K. Yuen (trimmed-mean form) |
| Tips≠ | Resistant summary measures | Robust parametric mean comparison |
| Pirmavots≠ | 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 |
| Citi nosaukumi | 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 |
| Saistītās≠ | 5 | 2 |
| Kopsavilkums≠ | 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. |
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