Improved selection agents in plant protection by econometric analysis

  • E. Kharchenko
Keywords: protection of plants, econometrics, statistical analysis, correlation and regression analysis, agronomy, Microsoft Excel

Abstract

The upraised questions were being followed by chemical and biological pesticides which are about to protect particular plantations. Having accurate basis in precise analysis and researches the overall assessment in pesticide to be chosen, for exact greenery protection, referred to econometric assay. The scope of the disquisition is proposed to be taken into account not as far as very econometric assay but the graphic parsing as well. The analysis is about to be done in Microsoft Excel what should be provided to the better authenticity of the research with more choice efficiency in using plant protecting preparations.The econometric assay is offered to conduct a variety of investigated factors of dada series to improve the efficiency of biological and chemical agents.In order to choose the right calculating method of specific correlation indicators and regression analysis in MS Excel according to the mold is being formed in linear or curvilinear figure of exploring factors.The correlation and regression analysis computation is suggested to be performed in MS Excel which allows putting in a great deal of data in the same rage of cells with the results being responded instantly. Comparing the indicators in correlation and regression analysis which is the most effective in plant protection, and accurate assess of qualitative and quantitative indicators, i.e. correlation coefficient, toxicity, cost, etc.Finally, the proposed calculation program in correlation and regression analysis is reckoned for being appeared in all economy fields either for exploration or for particular purposes. The upraised questions were being followed by chemical and biological pesticides which are about to protect particular plantations. Having accurate basis in precise analysis and researches the overall assessment in pesticide to be chosen, for exact greenery protection, referred to econometric assay. The scope of the disquisition is proposed to be taken into account not as far as very econometric assay but the graphic parsing as well. The analysis is about to be done in Microsoft Excel what should be provided to the better authenticity of the research with more choice efficiency in using plant protecting preparations.The econometric assay is offered to conduct a variety of investigated factors of dada series to improve the efficiency of biological and chemical agents.In order to choose the right calculating method of specific correlation indicators and regression analysis in MS Excel according to the mold is being formed in linear or curvilinear figure of exploring factors.The correlation and regression analysis computation is suggested to be performed in MS Excel which allows putting in a great deal of data in the same rage of cells with the results being responded instantly. Comparing the indicators in correlation and regression analysis which is the most effective in plant protection, and accurate assess of qualitative and quantitative indicators, i.e. correlation coefficient, toxicity, cost, etc.Finally, the proposed calculation program in correlation and regression analysis is reckoned for being appeared in all economy fields either for exploration or for particular purposes.

References

Леснікова І.Ю. Основи роботи і вирішення задач сільського господарства в середовищі електронних таблиць Exsel: навч. посібник / І.Ю. Леснікова, Є.М. Харченко. – Дніпропетровськ: Пороги, 2002. – 147 с.

Дронов С.В. Многомерный статистический анализ: учебное пособие / С.В. Дронов. – Барнаул: Изд-во Алт. гос. ун-та, 2003. – 213 с.

Опря А.Т. Статистика (модульний варіант з програмованою формою контролю знань): навч. посібник / А.Т. Опря. – К.: Центр навч літ-ри, 2012. – 448 с.

Годин А.М. Статистика: учебник / А.М. Годин. – М.: Дашков и К, 2012. – 451 с.

Моделювання технологічних процесів у середовищі Microsoft Exsel: навч. посібник / [М.В. Терещенко, Є.М. Харченко, В.М. Ковшов, Ю. Леснікова, В.О. Петренко, О.І. Гогенко, Ф.К. Клименко]. – Дніпропетровськ: Пороги, 2005. – 266 с.

Васильєва Н.К. Методи й моделі оптимізації в економіці: навч. посібник. – Дніпропетровськ: РВВ ДДАУ, 2008. – 142 с.

Васильєва Н.К. Моделювання розвитку аграрних підприємств регіонального кластера сільського господарства // Агросвіт. – 2012. – № 8. – С. 11–14.

Самарець Н.М. Використання інформаційних технологій у статистич-ному аналізі даних для аграрних підприємств / Н.М. Самарець, Є.М. Харченко, Н.О. Чорна // Агросвіт. – 2013. – № 20. – С. 14–20.

Samarets N. Application of mathematical models of transportation problems for optimization of agroindustrial production / N. Samarets // The providing of sustainable development of agricultural sector for its innovative base: collective monograph. – Science and Education Ltd, SHEFFIELD, 2015. – P. 176–183.

Чорна Н.О. Використання кривих Лоренца для оцінки рівномірності розподілу сільськогосподарських угідь в еко-агровиробництві // Вісник Дніпропетровського державного аграрно-економічного університетe. – 2015. – № 1. – С. 73–76.

Lesnikova, I.YU., Kharchenko, YE.M. (2002). Fundamentals and solving problems of agriculture in the environment spreadsheet Exsel. Dnіpropetrovs’k: Porogi, 147.

Dronov, S.V. (2003). Multivariate statistical analysis. Barnaul: Altai State University, 213.

Oprya, A.T. (2012). Statistics (modular version with a programmable form of control knowledge). Kyiv: Centr uchbovoi lіteraturi, 448.

Godin, A.M. Statistics (2012). Moscow: Dashkov i K, 451.

Tereshchenko, M.V., Kharchenko, YE.M., Kovshov, V.M., Lesnіkova, I., Petrenko, V.O., Gogenko, O.I., Klimenko, F.K. (2005). Modeling of processes in an environment Microsoft Exsel. Dnіpropetrovs’k: Porogi, 266.

Vasilyeva, N.K. (2008). Methods and models of optimization in the economyc. Dnіpropetrovs’k: RVV DDAU, 142.

Vasilyeva, N.K. (2012). Modelling of agricultural enterprises of the regional agriculture cluster. Agrosvit, № 8, 11–14.

Samarets, N.M., Kharchenko, YE.M., Chorna, N.O. (2013). Use of information technology in statistical analysis of data for agricultural enterprises. Agrosvіt, № 20, 14–20.

Samarets, N. (2015).Application of mathematical models of transportation problems for optimization of agroindustrial production. The providing of sustainable development of agricultural sector for its innovative base: collective monograph. Science and Education Ltd, SHEFFIELD. 176–183.

Chorna, N. (2015). Use of evaluation Lorenz curve uniform distribution of agricaltural lands for eco-agroproduction. News of Dnipropetrovsk State Agrarian and Economic University. 1(35), 73−76.

Section
Economics sciences