Learning outcomes:

Data analysis is the process of collecting, modeling, and analyzing data to extract insights that support decision-making. There are several methods and techniques to perform analysis depending on the industry and the aim of the analysis.The course aims to familiarize the students of the Department of Economics in gaining a better understanding of different techniques for data analysis, and methods in quantitative research

On successful completion of this module students will be able to:

  • Describe data analysis processes.
  • Use data software package in the implementation of data analysis techniques.
  • Understand appropriate statistical measures for various types of data.

Critically evaluate and assess the results of data analysis approaches.


  • Code :             X22
  • Semester :     2nd
  • Effort :              7.5 ECTS
  • Hours :             3 per week + 1 Lab
  • Type :                Mathematics
  • Department : Economics
  • Exams :             Yes

Course Contents:

  • Introduction to Essential types of data analysis methods
    • Cluster analysis.
    • Cohort analysis
    • Factor analysis.
    • Big data analysis
    • Individual data analysis
  • Introduction to major analysis techniques
    • Data cleaning
    • Data management
    • Data visualisation
    • Data interpretation
    • Data analysis tools

Preparing an economic analysis plan

  • Determinants, properties, and applications.
  • Linear transformations.
  • Eigenvalues and eigenvectors, matrix diagonalization.
  • Ιntroduction to MATLAB and applications to all above topics.