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Deskriptivna statistika×Kolmogorov-Smirnovljev test×
PodručjeStatistikaStatistika
ObiteljHypothesis testHypothesis test
Godina nastanka19771933
TvoracJohn W. TukeyAndrey Nikolaevich Kolmogorov; Nikolai Vasilyevich Smirnov
VrstaSummary procedureNonparametric goodness-of-fit test
Temeljni izvorTukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83–91. link ↗
Drugi nazivisummary statistics, exploratory data summary, Betimsel İstatistikKS test, K-S test, one-sample KS test, Kolmogorov-Smirnov Testi
Srodne62
SažetakDescriptive 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 Kolmogorov-Smirnov (KS) test is a nonparametric goodness-of-fit test that assesses whether a sample comes from a specified theoretical distribution, such as the normal or exponential. First formalised by Andrey Kolmogorov in 1933 and further developed by Nikolai Smirnov in 1948, it compares the empirical cumulative distribution function of the observed data against a target theoretical CDF and quantifies their maximum absolute deviation.
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ScholarGateUsporedite metode: Descriptive Statistics · Kolmogorov-Smirnov Test. Preuzeto 2026-06-19 s https://scholargate.app/hr/compare