No abstract

The relationships of intellectual signs with selfesteem and emotional characteristics of 5-7-year old preschoolers are studied. For this purpose, traditional methods of diagnostics were used: "Method of Express Diagnostics of Intellectual Abilities (MEDIA)", "Ladder", "House. Tree. Man", "Choose the right person". The research was based on preschool institutions in Moscow and Cheboksary. Correlation, factor analysis, and artificial neural networks were used to process psychological testing data and evaluate the relationships between different psychological indicators. It is shown that even with a small sample of respondents, such a comprehensive data mining allows detecting new features in the conditions when the results of testing of preschool children have integer scales with a limited range of values. Some gender features in intellectual indicators and their interrelations with emotional and personal characteristics are revealed. On the basis of quantitative data analysis, the most significant subtests and symptom complexes from the used methods were identified. The results obtained allow demonstrating the possibilities and advantages of using artificial neural networks for processing psychodiagnostic data. The tools used are available to practical psychologists because they are part of most modern software packages for statistical data processing.