Advance Statistics

Duration Time 13 weeks
Certificate no
Lessons 0
Course features
Elective 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.
His research interests are focused on the economics of food policy and quality, modelling agricultural markets and on Common Agricultural Policy issues.
Course Content

This course presents multivariate methods of analysis which is a powerful tool for the students. The course offers both the theoretical background and the practical aspects of the methods that will be taught.

With the successful competition of this course the students will be able:

  • To apply the basic methods of multivariate statistical analysis.
  • To implement the statistical inference for multivariate data
  • Use methods to reduce the dimensions of a problem.

Having acquired these qualifications students will be able to:

  • have proven knowledge and understanding of topics in Applied Statistics, which is based on their general secondary education and, while supported by advanced scientific textbooks, includes views arising from current developments at the forefront of their field of knowledge.
  • use the knowledge and understanding they have acquired in a way that demonstrates a professional approach to their work or profession and have skills that are typically demonstrated by developing and supporting arguments and problem solving within their field of knowledge.
  • have the ability to gather and interpret empirical data to formulate judgments involving reflection on relevant socio-economic, and scientific issues in general.

Course Layout  (EN)

Course Layout (EL)