Introduction
The foundation of statistical analysis is based on the randomness of samples. Although nonparametric methods have less restrictive data requirements, nevertheless, they all depend on the randomness of the sample points. Therefore, it is essential to be able to determine if the observations from a sample are random. Similar to tests of normality, the only tests available for randomness are nonparametric in nature.
A characteristic of random events is that they are not estimable or predictable. Therefore, it is worthwhile to determine whether sample points are random, yet it is easier to demonstrate what is not random rather than attempting to define randomness. For example, the closing prices of stocks fluctuate ...
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