Abstract
This chapter deals with nonparametric hypothesis tests that can be used when the specified parametric form of the underlying distribution cannot be assumed. It will not be assumed that the underlying distribution is normal, or exponential, or any other given type because no particular parametric form for the underlying distribution is assumed, such tests are called nonparametric. Nonparametric test resides can be applied without any assumption on the form of the underlying distribution. The chapter also considers the hypotheses concerning the median of a continuous distribution and illustrates how the sign test can be used. The two sample problem, where data from two separate continuous distributions can be used to test the hypothesis that the distributions are equal and the rank sum test is also presented in the chapter. The runs test can be used to test the hypothesis that a sequence of 0's and 1's constitutes a random sequence that does not follow any specified pattern is also described.
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