DATA ANALYSIS

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.

Features

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

FULL course outline

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