Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Aprakstošā statistika× | Kolmogorovs-Smirnova tests× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1977 | 1933 |
| Autors≠ | John W. Tukey | Andrey Nikolaevich Kolmogorov; Nikolai Vasilyevich Smirnov |
| Tips≠ | Summary procedure | Nonparametric goodness-of-fit test |
| Pirmavots≠ | Tukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165 | Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83–91. link ↗ |
| Citi nosaukumi≠ | summary statistics, exploratory data summary, Betimsel İstatistik | KS test, K-S test, one-sample KS test, Kolmogorov-Smirnov Testi |
| Saistītās≠ | 6 | 2 |
| Kopsavilkums≠ | 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 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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