Nonparametric tests of conformity. A guide to application

The monograph discusses the application of nonparametric goodness-of-fit tests (Kolmogorov, Kuiper, Kramer-Mises-Smirnov, Watson, Anderson-Darling, Zhang) in testing simple and complex hypotheses. Tables are provided in the appendix, containing percentile points and distribution models of statistics necessary for the correct use of the tests in testing simple and, most importantly, various complex hypotheses. Compared to the first edition, more attention is paid to the application of tests in non-standard conditions, particularly for analyzing large sample sizes. It is shown that the properties of the tests in applications can significantly change due to rounding errors, which must be taken into account when forming statistical conclusions. Following the recommendations in data analysis will ensure the correctness of statistical conclusions and increase their validity. The book is aimed at specialists who deal with statistical data analysis, processing experimental results, and applying statistical methods to analyze various aspects and trends of reality to some extent. It will be useful for engineers, researchers, professionals of various profiles (medical professionals, biologists, sociologists, economists, etc.), university professors, graduate students, and students. 2nd revised and expanded edition.