M.Sc. in Statistics



The postgraduate program of M.Sc. in Statistics provides specialized knowledge at postgraduate level to graduates of Greek and foreign Universities in the basic fields of Statistics and Probability.

The program’s objective is to train postgraduate students to the following fields:

Classes take place 4 mornings per week.


The study program mainly aims at full training and specialization of scientists with statistical or mathematical knowledge, in the science of Statistics and its applications, in order to be able to deal with and solve various problems in a quantitative way, both in the public and private sector.


During the first semester there are 4 obligatory courses offered. In the second semester, there are 3 course groups (Applied Statistics, Computational Statistics, Stochastics), each including 5 courses. Students choose two course groups and four courses out of each group.


The full study guide for the academic year 2022-23 can be found here.


1st Semester


Probability and Statistical Inference (7,5 ECTS)

Computational Statistics (7, 5 ECTS)

Generalized Linear Models (7,5 ECTS)

Data Analysis (7,5 ECTS)


2nd Semester

Applied Statistics

OPTIONAL (4 out of 5 courses)
Biostatistics (4 ECTS)

Advanced Methods in Survey Sampling (3,5 ECTS)

Statistical Process Control (3,5 ECTS)

Epidemic Models (4 ECTS)

Topics in Applied Statistics: Bioinformatics (3,5 ECTS)

Computational Statistics

OPTIONAL (4 out of 5 courses)
Bayesian Statistics (4 ECTS)

Statistical Learning (4 ECTS)

Statistics for big Data (3,5 ECTS)

Advanced Stochastic Processes (3,5 ECTS)

Applied Stochastic Modeling (3,5 ECTS)


OPTIONAL (4 of 5 courses)
Probability Theory (4 ECTS)

Time Series (4 ECTS)

Stochastic Modeling in Finance (3,5 ECTS)

Financial Econometrics (3,5 ECTS)

Stochastic Models in Operations Research (3,5 ECTS)

​3rd Semester

Thesis Writing (30 ECTS)

You can find a short description of the courses here.

Proclamation for the academic year 2022 - 23.

Probability Theory
Statistical Inference
Applied Statistics
Computational Statistics and Big Data
Theory and Applications of Stochastic Processes