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Statystyka opisowa×Test niezależności chi-kwadrat Pearsona×
DziedzinaStatystykaStatystyka
RodzinaHypothesis testHypothesis test
Rok powstania19771900
TwórcaJohn W. TukeyKarl Pearson
TypSummary procedureNonparametric association / goodness-of-fit
Źródło pierwotneTukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165Pearson, 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 ↗
Inne nazwysummary statistics, exploratory data summary, Betimsel İstatistikchi-squared test, χ² test, Ki-Kare Testi, chi-square test
Pokrewne63
PodsumowanieDescriptive 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.
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ScholarGatePorównaj metody: Descriptive Statistics · Chi-square goodness-of-fit test. Pobrano 2026-06-15 z https://scholargate.app/pl/compare