A description of the typical structure and typology of simulation models, which are used for educational and research purposes in population ecology at V. N. Karazin Kharkiv National University. These models decide whether there is a certain set of reasons sufficient to explain the appearance of a certain characteristic of the system under study and what are the conditions for the occurrence of these reasons. Type I models determine the dynamics of a certain process, which occurs under certain initial conditions. Type II models establish the probability distribution of simulation results over a series of iterations under identical input values, parameters, and experimental conditions. Type III models determine the influence of various combinations of initial parameters of simulation modeling on the probability distribution of its results. Type IV models iterate through and store in the form of a multidimensional array the results of simulations with different combinations of key parameters, which allows you to establish which of these combinations correspond to certain simulation results. Using the R programming language, we created the Simpson's Paradox model as an example of the types of models considered. This model explains the phenomenon of the expansion of altruistic behavior and helps identify the specific conditions under which altruists can succeed in a hypothetical population. It has been shown that in many cases group selection in a subdivided population can outperform individual selection. The authors believe that the methods used to build the discussed models can be useful for solving a number of other research problems.