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| Robustti frekvenssianalyysi× | Robustit kuvailevat tilastot× | |
|---|---|---|
| Tieteenala | Tilastotiede | Tilastotiede |
| Menetelmäperhe | Hypothesis test | Hypothesis test |
| Syntyvuosi≠ | 1970s–1980s (foundations); applied to frequency analysis throughout the 1990s–2000s | 1960s–1970s |
| Kehittäjä≠ | Huber, Hampel, Wilcox and the robust statistics tradition | John W. Tukey, Peter J. Huber, Frank Hampel |
| Tyyppi≠ | Robust descriptive and inferential procedure | Resistant summary measures |
| Alkuperäislähde≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838 | Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165 |
| Rinnakkaisnimet≠ | robust count analysis, outlier-resistant frequency analysis, robust distributional analysis | resistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation |
| Liittyvät≠ | 3 | 5 |
| Tiivistelmä≠ | Robust frequency analysis applies outlier-resistant estimation and resampling or exact methods to the counting and tabulation of categorical data, reducing the distortion caused by extreme observations, sparse cells, or violations of large-sample assumptions that can make conventional frequency summaries misleading. | 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. |
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