Modernization of Pearson distribution for approximation of the bilateral distribution laws of experimental data

Abstract

The urgency of the issue is caused by needs of improving the accuracy and simplifying the approximation of experimental data laws for bilateral distribution. The main aim of the study: modernization of the Pearson method, which eliminates some of its disadvantages and simplifies the procedure for approximation of bilateral distribution laws of experimental data, taking both positive and negative values. The methods used in the study: calculations using the methods of probability theory and statistics, as well as the software MathCAD; methods of integral and differential calculus. The results: The authors have proposed the modernized Pearson distributions to approximate distribution laws of experimental data, taking positive and negative values, which can significantly simplify the procedure of approximation. Topographic classification of modernized Pearson distributions with use of coefficient of joint asymmetry and excess kurtosis instead of coefficient of excess is designed. The paper introduces the formulas for calculating numerical characteristics of the modernized Pearson distributions.

Keywords

• pearson distribution
• approximation of distribution laws
• density of probabilities distribution
• classification of distributions
• coefficient of joint asymmetry and excess