Increasing the reliability of the economic forecast by checking the normality of the data array distribution

One of the errors in forecasting economic development trends is lack of initial normality check of data distribution as an essential condition for the applicability of statistical procedures. The applicability of these methods to distorted data results in inaccuracy and low quality of the economic forecast. The purpose of the study is to carry out a step-to-step normality check of data distribution to ensure a more accurate economic forecast based on the symmetry tests such as the coefficient of variation, quantile graphs, average absolute deviation, range of variation, and Jarque–Bera statistic. Data processing based on distribution of Russia’s gross domestic product from 2000 to 2020 revealed a normal array distribution, which ensures reliable economic forecasting and assessment of prospects for future changes in order to minimize errors and distorted results.