Agricultural Statistics and Biostatistics in Agriculture –A Basic Introduction
Mahamudul Hasan Millat
Science, Engineering & Technology School
Secretary, Rotaract Club of Khulna University
Agricultural Statistics and Biostatistics in Agriculture has enormous importance. Statistics is concerned with statistical methods for gathering, arranging, summarizing, presenting, and evaluating sample data, as well as drawing accurate conclusions on population characteristics and making rational decisions based on such an analysis.
The field of statistics:
Studying and using theories and techniques to analyze data that result from natural processes or phenomena. Trying to study how we make data sense:
The area of statistics includes some of the scientific method’s most basic methods and techniques:
- Hypothesis formation
- Design of experiments and observational studies
- derived from the data
- Overview of data
- Making data inferences (e.g. hypothesis testing)
Biostatistics is the branch of statistics application focused on health sciences and biology applications. Sir Francis Galton is the Father of Biostatistics. Biostatistics is often differentiated from the biometric field on the basis of whether applications are in the health sciences (biostatistics) or in wider biology (e.g. biometry; agriculture, ecology, wildlife).
Agricultural statistics play an important part in the sustainable development of the world. It has been believed conventionally that agricultural statistics take precedence around crop statistics.
Important aspects of Agriculture statistics as well as Biostatistics:
The following topics can be analyzed in Agriculture statistics as well as Biostatistics:
- Categorical analyzes of data, group trials, computer statistics
- Genetics of livestock, GWAS
- Ecological statistics, experiment design
- Study of decision-making, experiment design, multivariate methods
- Miscellaneous models, meta-analysis
Nature of Agricultural Statistics
To explain more thoroughly the essence of agricultural statistics, these may be grouped into the following major categories:
Irrigation and Land usage:
This includes the sown net area, gross cultivated field, current fallow, cultivable waste, non-current fallow, other uncultivated lands, kharif and rabi season irrigated area, etc.
This includes arable land, plantations, goats, and fisheries. It decides crop quality, crop yield, crop produced qualities. Statistics on agriculture provide information about various operations and different methods that can be implemented to increase crop production. It also helps to assess the various crop yields and crop quality tests.
Agricultural prices and wages:
Concepts on the intersection of wage rates are complex and conflicting. For rural poor policy planning, a clear understanding of the relationship between food prices and rural wages is important. Statistics on agriculture aid in this respect.
It addresses important methodologies such as ranked set sampling, adaptive cluster sampling, small area estimation, calibration-based estimators, experiment design, multivariate techniques, Internet of Things, and methods of ridge regression. It also includes the development of methodological techniques applied in forestry
For agricultural organization and farming structure:
Statistics relating to the organization of agriculture and the structure of farming, e.g. persons working in agriculture, their rank, land held under different tenure, number of draught animals, implements, farm building, etc.
For production and marketing Purpose:
Marketing and sales statistics and economics, e.g., production costs, input-output ratio, marketing shifts, spread-over marketing, etc. General statistics, literacy among those working in agriculture, housing, and related healthcare also in this regard.
It includes both capture and aquaculture production of fish, aquatic mammals, plants, and other aquatic animals, taken for commercial, industrial, recreational, and subsistence purposes from inland, brackish and marine waters. Data refer to all industrial, artisanal, and subsistence fisheries, excluding aquaculture. It should also exclude data on discards.
- Dorward, A. (2013). Agricultural labor productivity, food prices and sustainable development
impacts and indicators. Food Policy, 39, 40–50. https://doi.org/10.1016/j.foodpol.2012.12.003.
- HANDBOOK ON Agricultural Cost of Production Statistics Guidelines for Data Collection, Compilation and Dissemination