Introduction
Course Description
Agricultural statistics training and instruction are crucial in improving global agricultural systems. Farmers and agricultural practitioners are now keen to prowess in research and learning in agricultural statistics and computer applications. Understanding recent statistical applications for descriptive and predictive analyses on yield and productivity is vital for their existence and this knowledge helps farmers make better statistical assumptions. This course explores to the industry key insights to develop a broader and deeper understanding and a strong comprehension of essential principles of data and statistics in agriculture, with an emphasis on used examples and possible impact. Foundations are covered first, followed by agricultural applications. Candidates learn forecasting approaches to boost production, efficiency, and competitiveness. Analysis methodologies using soft tools are covered which educate farmers boost their farm output.
Course Content
- Index Numbers & Forecasting
- Forecasting Techniques in Agriculture
- Analysis of VAriance
- Regression Path Analysis
- Multivariate Analysis
- Stability and Sustainability Analysis
Course Audience
- Farmers attempting to increase yield
- Faculty of Agriculture Universities
- Professionals at State and Central Departments of Agriculture
- NGOs in Agriculture
- Undergraduate and Graduate Students of Agriculture and Allied Sciences
- Agriculture Scientists at ICAR
- KVK Specialists
- Progressive Farmers/Farming Community
Outcomes of this Course
- Identify the statistical analysis techniques for their data
- Select agricultural forecasting techniques
- The fundamentals of statistics for use in agriculture
- Knowledge of regression and multivariate analysis soft tools
