Сравнение методов

	Робастные описательные статистики	Анализ мощности
Область	Статистика	Статистика
Семейство	Hypothesis test	Hypothesis test
Год появления	1960s–1970s	1969 (1st ed.); 1988 (seminal 2nd ed.)
Автор метода	John W. Tukey, Peter J. Huber, Frank Hampel	Jacob Cohen
Тип	Resistant summary measures	Sample size and power planning
Основополагающий источник	Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832
Другие названия	resistant statistics, outlier-resistant summary statistics, robust summary measures, robust location and scale estimation	sample size calculation, power calculation, sensitivity analysis, a priori power analysis
Связанные	5	5
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.	Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study.