Dimara Efthalia
Professor
Field of Expertise:
Applied Statistics, Data Analysis
Organic Unit / Lab:
Laboratory of Quantitative Economics and Information Systems
E-mail:
Telephone:
Office Hours:
Wednesday 13.30 - 15.30
Data analysis by wynpnt@pixabay
The aim of the course is to enable students to expand and deepen their knowledge and skills in various areas of statistics and of statistical analysis of large data sets.
After completing the course the student will:
Lectures (3 hours per week) and Laboratory work (1 hour per week)
Activity |
Semester workload |
Lectures |
(3 x 13=) 39 hours |
Laboratory work |
(1 x 13=) 13 hours |
Self-study and project preparation |
98 hours |
Total number of hours for the Course (25 hours of work-load per ECTS credit) |
150 hours (total student work-load) |