Home > Projects/Reports > AGRICULTURAL SCIENCE STUDENTS-Statistics


Statistical education for agriculturists tries to give them a solid foundation in statistics. An emphasis is placed on mastering a wide use of statistical method in order to allow the students to apply these techniques in many fields of agricultural science like: field crops production, vegetable crop production, horticulture, fruit growing, grape production, plant protection, livestock, veterinary medicine, agricultural mechanization, water resources, agricultural economics etc.


The agricultural investigations are based on the application of statistical methods and procedures which are helpful in testing hypotheses using observed data, in making estimations of parameters and in predictions. The application of statistical principles and methods is necessary for effective practice in resolving the different problems that arise in the many branches of agricultural activity. Because of the variability inherent in biological and agricultural data, knowledge of statistics is necessary for their understanding and interpretation. Numerous activities in agriculture are very different from each other, resulting in different branches of agricultural science like: field crop production, vegetable production, horticulture, fruit growing, grape production, plant protection, livestock, veterinary medicine, agricultural mechanization, water resources, agricultural economics etc.

The importance of statistical science in agriculture is obvious, where the collection, analysis and interpretation of numerical data are concerned. Statistical principles apply in all areas of experimental work and they have a very important role in agricultural experiments. Statistics plays an important role in experimentation, while many scientific problems could be solved by different statistical procedures.


Modern agricultural production is characterized’ by some particularities and many different activities. So, it arises different problems and different nature of agricultural materials data which require different approaches to the use of statistical methods. Statistics is a discipline which mainly deals with data quantifications. Even in the case of nonnumerical data, statistical methods use transformations to change nonnumerical data to numerical data, with the aim of achieving some level of quantification to make conclusions about the matter of interest. Many data in agriculture are of numerical character which are accompanied with the existence of the variability of data. Variability is a characteristic of biological and agricultural data. Statistics can be used as a tool for research, spreading in many fields of research, like in agronomy. For these reasons “statistics can, however, help the research worker to design his experiments and to .evaluate objectively the resulting numerical data.

Scientists use statistics as a tool, which, when correctly applied, is of enormous assistance in the study of the laws of science (Bethea, Dmaiy& Rnullion;108-S). It is important to emphasize that there are no statistical procedures which are applicable only to specific fields of study. There are general statistical procedures which are applicable to any branch of knowledge in which observations are made.

There are many problems at the Agricultural Faculty that have been elaborated through statistical methods. Some of examples of the use of statistics are related to: crop farming (wheat, maize, sugar beet, sunflower, soy, fodder crops, other industrial crops etc), vegetable crops (potatoes, tomatoes, beans, peas, onions, peppers etc), fruit growing (apples, pears, plums, cherries, sour cherries, apricots, peaches, walnuts etc), viticulture (grapes), horticulture plants, perennials, livestock breeding (cattle breeding, pig breeding, sheep breeding, poultry breeding), exploitation of agricultural machines and transport means, utilization and protection of waters, consumption of mineral fertilizers, consumption of plant protection preparations etc. Problems related to agricultural economics are: agricultural population, cultivable area, agricultural enterprises and cooperatives, individual (private) holdings, workers in agricultural enterprises and cooperatives, costs, sources of income etc.

Some examples of the application of statistical methods in problems through research processes are: genetics and plant breeding, crop production concerning different conditions of agrotechnics and plant protection, type of soils, localities, varieties, sorts, hybrids, conditions of irrigation, use of herbicides, plant physiology, plant biochemistry, genetics and livestock breeding, animal physiology, livestock production concerning different races, different conditions of animal nutrition, protection ,etc. Some other examples of the use of statistics are related to: the method of production functions in wheat, maize and sugar beet production, etc, the influence of particular factors on agricultural production measuring of contribution of production factors and technical progress to the growth of national product tendencies of production lines in agriculture, etc.


“Every practical statistical analysis is directed toward establishing a probability model of an appropriate level of complexity, which can then be used to make “predictions” in some sense, on the basis of which decisions can be made.

The statistical education of agriculture students is very important for many reasons. The study of statistics is helpful in experimental work both for the analysis of the data and for the design of the experiment in such a way that valid and efficient results are produced. It is obvious that statistical methods are useful for students who are preparing themselves for specialization in their field. Statistical methods used in agricultural science are useful also for better understanding and explanation of causal relations between existing phenomena.

A course of statistics for students in the biology groups: field and vegetable crops, fruit growing, grape production, horticulture, plant protection, livestock and veterinary medicine covers one semester.


Fertilizer and pesticide use needs to be monitored, this is done by checking the usage on individual crops.


The service is also committed to educating the relevant people by producing regular publications which provide not only statistics but also useful information on regulations and new programs that are being introduced. NASS takes on board what their stakeholders have to say and follow these recommendations, so their role is not only about producing statistics for the agricultural markets, but also assisting in producing a higher quality of products.


Agriculture statistics in the countries dominated by agriculture imply that Agriculture industry contributes approximately 24% of the GDP or Gross Domestic Products. It helps us to compare the different yields of crops, quality check of crops compared to the quality of crops produced in other parts. It furnishes a rough outline of the incidence of various operations with regard to the Agriculture industry.


Everything in agriculture is statistics in some way, from the science to make it to the return investment the farmer will mat the most fundamental level, statistics allows us to calculate averages, ranges, and standard deviations


Statistics in agriculture are essential for conducting research and comparing management strategies such as selecting a crop variety, or applying appropriate amounts of fertilizer.

Because agriculture involves many variables, determining if a response is related to a change in management or another variable is crucial. Statistical analysis allows researchers to more effectively understand relationships between management factors in agricultural varieties or which fertilizer treatments will give better yields than others.


It has describe briefly Statistical education and training of agricultural students is designed for different  groups. It has emphasized the importance of the use of statistical methods which could be applied in research work.

  • Bethea, R.M., Duran, B.S., & Bouillon, T.L. (1985). Statistical methods for engineers and
  • scientists. New York: Marcel Dekker.                      ‘
  • Box, G.E.P., Hunter, W.G., & Hunter, J.S. (1978). Statistics for experimenters, an introduction to
  • design, data analysis and model building. New York: John Wiley & Sons.

Related Posts

Leave a Comment

2 + 17 =