Comparer des méthodes

	Statistiques descriptives	Test d'indépendance du Khi-deux de Pearson
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1977	1900
Auteur d'origine	John W. Tukey	Karl Pearson
Type	Summary procedure	Nonparametric association / goodness-of-fit
Source fondatrice	Tukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165	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.
Alias	summary statistics, exploratory data summary, Betimsel İstatistik	chi-squared test, χ² test, Ki-Kare Testi, chi-square test
Apparentées	6	3
Résumé	Descriptive statistics is a set of procedures that numerically and visually summarises the essential characteristics of a dataset: central tendency (mean, median, mode), spread (standard deviation, interquartile range), shape (skewness, kurtosis), and frequency distributions. Systematised for applied data analysis by John W. Tukey in his 1977 work on Exploratory Data Analysis, descriptive statistics serves as the indispensable first step before any inferential or modelling procedure.	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.