Features of the Method of Iteration of Means in Studying Populations

This article considers the features of the mean iteration method when studying populations the quantitative indicators of which have different statistical distributions. The studies were conducted in the central part of the Northwest Caucasus. The published and field data used by the authors came from eight sample plots laid out in the lower mountain, forest–steppe, and steppe zones of the central part of the region, where various indicators were studied for seven plant species. The sample size in the sample plots was 122–485 individuals. Statistical data processing was carried out using the Stadia8.0 and Microsoft Excel for Windows programs. The values of inter-iteration means and gradations were established using known and original methods. It was revealed that, with a normal statistical distribution, the inter-iteration means have close values (difference of 0–4.23%) with the values of the means increased by 0.5–2 standard deviations. To correct extreme inter-iteration values, where the sample is insignificant (1–4 observations), it is recommended to use forecast models, which should be calculated separately for each option. The allocation of gradations of quantitative traits in populations by the iteration of means method ensures an adequate distribution of indicators in three or five gradations compared to methods focused on the average increased by the value of the standard deviation or dividing the indicators into equal values.