Quantitative Methods

Duration Time 13 weeks
Certificate yes
Lessons 0
Course features
Compulsory Course
Credits : 5
RE&D Department
Lecture Hours : 5
Lab Hours : 0
Autumn Semester
Assistant Professor
His primary research interests include the application of classical and newer statistical/econometric methods and approaches in the following scientific fields: Environmental data, environmental economics, epidemiological data with emphasis on zoonoses and their transmission mechanisms in space and time, sustainable development, environmental responsibility, sustainability indicators, forestry data.
Course Content

The aim of the course is to offer the students mathematical knowledge, not taught in the general Mathematics courses of the first two semesters, with a special emphasis on economic analysis and agricultural economics. Students will be taught and learn applications of these methods both in exploring theory and developing practice, as well as in solving specific financial problems faced by businesses or policy-making. Students are expected to understand the necessity of the previous mathematical knowledge they have acquired and which they will practice again, and they will be able to judge and decide what specific mathematical methods and tools taught in this course are suitable for solving specific problems. Application of the methods will be assisted with exercises and examples.

Applications of these mathematical methods are expected to:

  • improve the student’s perception of theoretical and practical problems as well as their judgment for solving optimization problems with applications especially in agricultural economics.
  • being able to communicate information, results and solutions based on the application of appropriate mathematical optimization methods (maximization / minimization problems) to both specialized and non-specialized audiences.

In addition, to acquire the necessary basic knowledge in mathematical optimization that will undoubtedly be needed by those who decide to continue with postgraduate / doctoral studies and research.

Course Layout  (EN)

Course Layout (EL)