Nonparametric statistics provide a scientific methodology for cases
where customary statistics are not applicable. Nonparametric
statistics are used when the requirements for parametric analysis
fail, such as when data are not normally distributed or the sample
size is too small. The method provides an alternative for such
cases and is often nearly as powerful as parametric statistics.
Another advantage of nonparametric statistics is that it offers
analytical methods that are not available otherwise. Nonparametric
methods are intuitive and simple to comprehend, which helps
researchers in the social sciences understand the methods in spite
of lacking mathematical rigor needed in analytical methods
customarily used in science. This book is a methodology book and
bypasses theoretical proofs while providing comprehensive
explanations of the logic behind the methods and ample examples,
which are all solved using direct computations as well as by using
Stata. It is arranged into two integrated volumes. Although each
volume, and for that matter each chapter, can be used separately,
it is advisable to read as much of both volumes as possible;
because familiarity with what is applicable for different problems
will enhance capabilities.
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