[Detection and considering of nonlinear effects in regression modeling].

One of the basic problems solved in the research work is the search for causal relationships between the variables analyzed. Very important, but not the only requirement for the existence of causality is to demonstrate the occurrence of a statistically significant correlation and determine the shape of the present relationship (regression). In the vast majority of experimenters limited to the study of linear associations. The paper presents one of the simplest but effective method of enriching models with nonlinear terms.