The first systematic introduction to statistical inference theory for the case where raw data are converted to ranks, resulting in nonparametric estimation and statistical inference procedures. One-and two-sample models of arbitrary and symmetric continuous distributions, analysis of variance with two-sided classification, rank correlation theory and theory of linear regression models are considered. An introduction to statistical inference theory for multidimensional data is given. For statisticians, computer center workers, as well as undergraduate and graduate students of universities.