EVALUATION AND ANALYSIS OF DYNAMICS OF EFFICIENCY GRAINS AND LEGUMES

Abstract

Goal. Described using histograms accumulation, charts, bubble charts volumetric changes of gross yield, yield and acreage of grain and leguminous crops in the federal districts of Russia during the past 5 years. Factor analysis of the effect of yield and acreage to changes in gross collection. Built equation for forecasting the gross harvest of grain and leguminous crops. Methods. We used the methods of descriptive statistics, visualization, factor analysis, correlation and regression analysis. Results. To identify differences between the federal districts were summarized figures for gross harvest, yield and sowing areas of grains and leguminous plants in the federal districts of Russia during the past 5 years. It is possible to trace the trend of these changes in the indices of all FD (as well as the relative position of FD), not only for one year, but for the last 5 years at the same time with the help of histograms and graphs accumulation. Bubble charts clearly demonstrated the interdependence of all three indicators that statistical calculations has been confirmed in the future. Factor analysis showed the importance of the influence of yield and acreage on the gross yield of grain and leguminous crops in the federal districts of Russia. Conclusion. Using the methods of descriptive statistics, visualization, factor analysis, correlation and regression analysis demonstrated their great potential for the evaluation and analysis of the dynamics of a production efficiency of grain and leguminous crops. On the basis of descriptive statistics and visualization techniques have been investigated location of each FD in the development of culture as the data over time and relative to other FD. It has been made appropriate recommendations on the priorities for each DOF. On the basis of factor analysis, it was concluded that the yield of grain and leguminous crops in the Federal District received much attention, it is impossible fully to the increase in acreage. The calculated multiple regression equation allows you to make forecasts of gross collection and suggests that the productivity effect on the gross yield is much more significant than the impact of acreage.