Personal well-being has been actively studied over the past two decades regarding the social practice demands. However, it is an extremely complex multi-concept which is difficult to verify. The article analyzes the mathematical and statistical methods used in Ukrainian studies of the phenomenon of personal well-being over the past five years. Firstly, the study shows that in domestic publications (especially articles) the importance is not given to the mathematical and statistical methods.

Secondly, typical tasks in the study of personal well-being are the description of primary data, the study of similarity (Student’s t-test, Mann-Whitney’s U-test, Kraskal-Wallace’s H-test, Wilcoxon’s T-test, ANOVA) and the study of dependencies (Pearson’s correlation coefficient, Spearman’s rank-order correlation coefficient).

Thirdly, correlation analysis is still one of the main analysis statistical tools over the past five years according the study of the links between well-being and other psychological phenomena. Since well-being is a highly complex system characterized by the presence of recurrent relationships and nonlinearity, it is important to use the synergetic paradigm and modern mathematical and statistical means of data analysis (Data mining), which allow to characterize systems characterized by ambiguity and uncertainty.

Fourthly, application of new modern statistical methods is not yet widespreaded. When studying the phenomenon of personal well-being, the practice of processing small databases within the framework of applied statistics continues. Structural modeling, which makes it possible to confirm multidimensional models of well-being, is not widespreaded.

Application of Bayesian networks of trust is quite promising, which are based on the concept of subjective probability, thus it is focused not on the study of objective reality, but on clarifying the individual’s ideas about it.

Key words: psychological well-being, mathematical and statistical analysis, subjective well-being, modeling, personal well-being.

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