Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Aprakstošā statistika× | Pirsonas neatkarības hi kvadrāta tests× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1977 | 1900 |
| Autors≠ | John W. Tukey | Karl Pearson |
| Tips≠ | Summary procedure | Nonparametric association / goodness-of-fit |
| Pirmavots≠ | 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. link ↗ |
| Citi nosaukumi≠ | summary statistics, exploratory data summary, Betimsel İstatistik | chi-squared test, χ² test, Ki-Kare Testi, chi-square test |
| Saistītās≠ | 6 | 3 |
| 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 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. |
| ScholarGateDatu kopa ↗ |
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