Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест Пирсона на независимость с использованием критерия хи-квадрат× | V-крамера× | |
|---|---|---|
| Область | Статистика | Статистика |
| Семейство | Hypothesis test | Hypothesis test |
| Год появления≠ | 1900 | 1946 |
| Автор метода≠ | Karl Pearson | Harald Cramér |
| Тип≠ | Nonparametric association / goodness-of-fit | Nonparametric association measure |
| Основополагающий источник≠ | Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables. Philosophical Magazine, Series 5, 50(302), 157–175. link ↗ | Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press. ISBN: 978-0691080420 |
| Другие названия | chi-squared test, χ² test, Ki-Kare Testi, chi-square test | cramers v, cramer v, phi coefficient (r×c), Cramer's V (İlişki Kuvveti) |
| Связанные | 3 | 3 |
| Сводка≠ | The chi-square test of independence is a nonparametric hypothesis test that determines whether two categorical variables are statistically associated or independent of one another. Introduced by Karl Pearson in 1900, it remains the standard procedure for analysing contingency tables and requires no assumption of normality — only that observations are independent and that expected cell frequencies are sufficiently large. | Cramer's V is a nonparametric effect-size statistic that measures the strength of association between two categorical variables on a scale from 0 to 1. Introduced by the Swedish mathematician Harald Cramér in his 1946 work Mathematical Methods of Statistics, it generalises the phi coefficient to tables of any size, making it the standard companion statistic to the chi-square test. |
| ScholarGateНабор данных ↗ |
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