Nonparametric methods (CROSBI ID 583736)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
Sporiš, Goran
engleski
Nonparametric methods
In Performance Analysis the data gathered and processed are, in most cases, nonparametric by nature. A clear understanding of these different processes, and their respective advantages and disadvantages must be mastered by all Performance Analysts. These processes should be used for both testing the reliability of our data gathering systems, and also for comparing sets of data to determine significant differences or otherwise. The following tests will be discussed:- Sign Test, Wilcoxon Signed-Rank Test, Mann-Whitney-Wilcoxon Test, Kruskal-Wallis Test and Rank Correlation. Most of the statistical methods referred to as parametric require the use of interval- or ratio-scaled data. Nonparametric methods are often the only way to analyze nominal or ordinal data and draw statistical conclusions. Nonparametric methods require no assumptions about the population probability distributions. Nonparametric methods are often called distribution-free methods. In general, for a statistical method to be classified as nonparametric, it must satisfy at least one of the following conditions: The method can be used with nominal data. The method can be used with ordinal data. The method can be used with interval or ratio data when no assumption can be made about the population probability distribution. All these principles will be discussed with each of the tests, examples from sport science introduced and analysed, the the respective pitfalls and advantages explained.
nonparametric methods
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Podaci o prilogu
37-37.
2011.
objavljeno
Podaci o matičnoj publikaciji
6th INSHS International Christmas Sport Scientific Conference : abstracts
Hughes , Mike ; Dancs, Henriette
Szombathely: INSHS
Podaci o skupu
6th INSHS International Christmas Sport Scientific Conference
ostalo
11.12.2011-14.12.2011
Szombathely, Mađarska