Ibragim Suleimenov ¹ Mariya Kostsova ² Anastasiya Grishina ³ Dinara Matrassulova ¹ Yelizaveta Vitulyova ^1*

• ¹ Al-Farabi Kazakh National University, Almaty, Kazakhstan
• ² Sevastopol State University, Sevastopol, Russia
• ³ V.I. Vernadsky Crimean Federal University, Simferopol, Russia

The problem of the adequacy of psychological testing methods, which are varieties of "projective techniques", is discussed. It is shown that this problem can be solved empirically by collecting of corresponded statistics. Based on experimental data, it is shown that the distribution of respondents' answers to a test in which they are asked to rank pictures in accordance with their own preferences is not homogeneous. Experimental data show that there are answer options that are statistically most common. An interpretation of testing is proposed in which passing the test is considered as "connecting" an external additional layer to the neural network formed by the respondent's brain. In accordance with this interpretation, the most frequently occurring answer options can be considered as the basis for the formation of classification characteristics. It is shown that during using tests of this type it is advisable to take into account the code distances between the answer of a particular respondent and the codes corresponding to the most frequently occurring sequences. It is shown that for quantitative processing of testing results in the case under consideration, it is advisable to use abstract algebra methods. A specific example of processing experimental data using such methods is presented. The possibilities of generating psychological tests directly based on experimental data and images generated by neural networks are discussed.