Sammenlign metoder
Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.
| Pearsons kikelighedstest for uafhængighed× | Cramérs V× | |
|---|---|---|
| Fagområde | Statistik | Statistik |
| Familie | Hypothesis test | Hypothesis test |
| Oprindelsesår≠ | 1900 | 1946 |
| Ophavsperson≠ | Karl Pearson | Harald Cramér |
| Type≠ | Nonparametric association / goodness-of-fit | Nonparametric association measure |
| Oprindelig kilde≠ | 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 |
| Aliasser | chi-squared test, χ² test, Ki-Kare Testi, chi-square test | cramers v, cramer v, phi coefficient (r×c), Cramer's V (İlişki Kuvveti) |
| Relaterede | 3 | 3 |
| Resumé≠ | 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. |
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