Department Profile

Agricultural Statistics

The Department of Mathematics and Statistics established in the year 2017 as an allied subject for B.Sc. (Hons.) Agriculture students. This department is in the division of Social Science. Mr. V.Sakthivel currently working as Assistant Professor, Department of Mathematics and Statistics. This department plays a Crucial Role in Agriculture by Providing Quantitative Tools and Analytical Methods to Solve Complex Problem Related to Crop production resource management environmental sustainability and agricultural economics.


I          Course code: MAT 111

Course Name & Credit Hours: Elementary Mathematics (1+1)


II         Course code: STA 201

Course Name & Credit Hours: Statistical Method (1+1)


Course Learning Rationale (CLR)

The purpose of learning this course is to:

CLR: 1 Develop and apply mathematical and statistical models to analyses agricultural data, including crop yields, climate patterns, soil properties, and other relevant variables. This helps in understanding trends, making predictions, and optimizing agricultural practices.

CLR: 2 Implement precision agriculture techniques by utilizing mathematical models and statistical analyses to optimize the use of resources such as water, fertilizers, and pesticides. This enhances efficiency and sustainability in farming practices.

CLR: 3 Use mathematical models to understand soil processes and environmental interactions affecting agriculture. This can include studying nutrient cycling, erosion, and the impact of climate change on crop production.

CLR: 4 Utilize econometric methods to analyses economic aspects of agriculture, such as market trends, pricing, and the economic impact of different agricultural practices. This supports informed decision-making in agricultural economics.

CLR: 5 Link mathematics with agricultural engineering

CLR: 6 comprehend the use of Slope-Intercept

CLR: 7 Device formulas for straight lines

CLR: 8 Integrate product of functions and define matrices and determinants


Course Learning Outcomes (CLO)

At the end of the course, learners will be able to:

CLO 1: Having an ability to apply mathematics and science in agricultural applications

CLO 2: Having a clear understanding of the subject related concepts and of contemporary issues

CLO 3: Having an ability to design and conduct experiments, as well as to analyze and interpret data

CLO 4: Having an ability to use techniques, skills and modern engineering tools necessary for agricultural practices

CLO 5: Having problem solving ability- solving farmers problems

CLO 6: Having cross cultural competency exhibited by working in teams

CLO 7: Having adaptive thinking and adaptability