Studies Program

Informative Brochure for the Undergraduate Studies Program in Statistics

  1. The courses in the program are divided into three main categories:
    1. 14 compulsory courses, which all students of the Department are required to attend;
    2. elective courses, offered by the Department of Statistics;
    3. free elective courses, which are divided into:
      1. courses offered by other Departments of the Institution
      2. Practical Training
  1. The compulsory courses are offered during the first six semesters of study (eight (8) in the first year, four (4) in the second year, and two (2) in the third year), so that students acquire the necessary background to make informed choices in the subsequent years.
  2. There are no compulsory courses in the final two semesters. This gives students the flexibility to design a study program that provides the core knowledge of Statistics (as covered by the compulsory Statistics courses), while also allowing them to tailor their program to their particular interests.
  3. In the first two semesters of study (1st + 2nd), students may register for courses carrying no more than 30 ECTS credits per semester.
  4. In the 3rd and 4th semesters, students may register for courses carrying no more than 40 ECTS credits per semester.
  5. In the 5th and 6th semesters, students may register for courses carrying no more than 40 ECTS credits per semester.
  6. In the 7th and 8th semesters, students may register for courses carrying no more than 48 ECTS credits per semester. In these semesters, an exception to this limit may be made only for the Practical Training.
  7. After the 4th year, students may register for courses carrying no more than 48 ECTS credits per semester. An exception to this limit may be made only for the “Practical Training”. Specifically, the registration limits by year of study are shown in the table below:

Maximum ECTS’s

Year

Winter Semester

Spring Semester

1st’

30 ECTS

30 ECTS

2nd’

40 ECTS

40 ECTS

3rd’

40 ECTS

40 ECTS

4rth’

48 ECTS + Practical Training

48 ECTS + Practical Training

5th and above

48 ECTS + Practical Training

48 ECTS + Practical Training

  1. When selecting courses for registration in each semester, priority must be given to compulsory courses from previous semesters that the student has not successfully completed and that are offered in the semester concerned.
  2. The program includes prerequisite courses. More specifically, the course “Estimation–Hypothesis Testing” offered in the 3rd semester is a prerequisite for the course “Linear Models” offered in the 4th semester. The course “Linear Models” offered in the 4th semester is a prerequisite for the courses “Data Analysis” offered in the 5th semester and “Generalized Linear Models” offered in the 6th semester. It should be noted that the courses “Estimation–Hypothesis Testing” and “Linear Models” are offered again in the 4th and 5th semesters of study, respectively.
  3. In addition to the 14 compulsory courses, which correspond to 108 ECTS credits, students must earn at least 84 ECTS credits from the elective courses offered by the Department in order to complete the remaining credit requirements. The remaining 48 ECTS credits required for the degree may be earned either from elective courses offered by the Department or from free elective courses offered primarily by other Departments of the University.
  4. The course “Practical Training” is an elective course. Therefore, the ECTS credits awarded for this course do not count toward the 84 ECTS credits required from elective courses offered by the Department.
  5. Transitional period for students enrolled under the previous undergraduate program: It is noted that the degree requirements previously applicable to students already enrolled in the program will remain in effect for a transitional period of four years. After the end of this four-year period, i.e. from the academic year 2030–2031 onward, all students of the Department’s undergraduate program will be subject to the same degree requirements (the requirements set out above).
  6. The list of courses offered is announced each year depending on the availability of teaching staff. Elective courses may not be offered in a particular academic year if no instructor is available.
  7. Upon completion of the degree, students may obtain a certificate of computer skills equivalent to ECDL for public-sector purposes, provided that during their studies they have successfully completed at least four of the following courses:

INFORMATICS KNOWLEDGE COURSES

Course Title

Department

INTRODUCTION TO PROGRAMMING USING R

STAT

INTRODUCTION TO PROBABILITY AND STATISTICS USING R

STAT

DATA ANALYSIS

STAT

COMPUTATIONAL STATISTICS AND SIMULATION (old title: Simulation)

STAT

NUMERICAL METHODS AND OPTIMIZATION IN STATISTICS AND MACHINE LEARNING (old title: NUMERICAL METHODS IN STATISTICS)

STAT

INTRODUCTION TO PROGRAMMING USING PYTHON

STAT

DATABASES, or INTRODUCTION TO DATABASE MANAGEMENT

DET OR INF OR STAT

COMMUNICATION NETWORKS

INF

COMPUTER NETWORKS

INF

DATA MANAGEMENT & ANALYSIS SYSTEMS

(old title: DATABASE DESIGN)

INF

ARTIFICIAL INTELLIGENCE

INF

MACHINE LEARNING

INF

DATA MINING AND DATA SCIENCE

(old title: DATA MINING)

INF

INFORMATION RETRIEVAL SYSTEMS

INF

  1. Students have the opportunity to enroll in the Study Program in Educational Sciences and Education. For more information, please visit: https://www.dept.aueb.gr/en/tep
  2. Finally, students can attend courses for one semester at a corresponding department at a university abroad through the ERASMUS+ program. Courses successfully completed by students are recognized as equivalent to courses in the Department’s study program and are included in their academic transcripts. For details on the student mobility procedure, please visit the Athens University of Economics and Business website: https://www.aueb.gr/en/erasmus

GENERAL STRUCTURE OF THE STUDY PROGRAM

The general structure of the study program is presented in the table below.

Α’ Εξάμηνο

Β’ Εξάμηνο

  • Probability Ι (C)
  • Calculus Ι (C)
  • Linear Algebra Ι (C) 
  • Introduction to programming using R (C)
  • Statistics I: Probability and Estimation*

  • Probability ΙΙ (C)
  • Calculus ΙΙ (C)
  • Linear Algebra ΙΙ (C)
  • Introduction to Probability and Statistics using R (C)
  • Statistical Inference and Regression *

Γ’ Εξάμηνο

Δ’ Εξάμηνο

  • Estimation and Hypothesis Testing (C)
  • Stochastic ProcessesΙ (C)
  • Introduction to Mathematical Analysis
  • Introduction to Programming with Python
  • Introduction to Operational Research
  • Introduction to Accounting Information Systems
  • ERASMUS BIP: Mixed Mobility for Studies**
  • Linear Models (Υ)
  • Time Series Analysis (Υ)
  • Demographic Statistics
  • Sampling
  • Mathematical Methods
  • Actuarial Science Ι

Ε’ Εξάμηνο

ΣΤ’ Εξάμηνο

  • Data Analysis (C)
  • Design and Analysis of Experiments
  • Statistical Quality Control
  • Theoretical Statistics
  • Bayesian Statistics
  • Advanced Sampling Methods
  • Multivariate Statistical Analysis
  • Generalized Linear Models (C)
  • Computational Statistics and Simulation
  • STPS: Quantitative Risk Management and Analytics
  • Probability Theory
  • Official Statistics
  • Biostatistics I
  • Numerical Methods and Optimization in Statistics and Machine Learning
  • STPS: Visualization and Data Story Telling
  • Introduction to Database Management

Ζ’ Εξάμηνο

Η’ Εξάμηνο

  • Methods of Statistical and Machine Learning
  • Biostatistics ΙΙ
  • Econometrics
  • Stochastic Processes ΙΙ
  • Actuarial Science ΙΙ
  • Methods of Bayesian Inference
  • Methodological Tools of Machine Learning
  • Bachelor Thesis
  • Practical Training
  • Categorical Data Analysis
  • Statistical Methods for the Environment and Ecology
  • Non-Parametric Statistics
  • STSP: Statistical Modeling of Complex Data
  • Measurement Theory with reference to Probability and Statistics
  • Statistical Decision Theory and Game Theory
  • Sports Data Analytics
  • Research Methodology
  • Bachelor Thesis
  • Practical Training

(C) Compulsory Course

Notes:

  • Courses marked with an asterisk (*) — “Statistics I: Probability and Estimation” and “Statistics II: Statistical Inference and Regression” — will be offered only to Erasmus+ students during the academic year 2026–2027.
  • The course marked with two asterisks (**) — “ERASMUS BIP: Blended Mobility for Studies” — will be offered only when a Multilateral Inter-Institutional Agreement is in place between universities, with specific selection criteria and for a specified number of students (funding provided by the State Scholarships Foundation – IKY). Students may participate in the program only once (1) during their studies, following a Call for Expressions of Interest.
  • Elective courses are offered only if a lecturer is available.
  • Tutorial classes are provided for all compulsory courses. Tutorials/laboratory sessions may also be offered for elective courses, subject to availability.
  • All courses consist of 4 hours of teaching and 2 hours of tutorial/laboratory sessions, where applicable.
  • The method of assessment is determined by the instructor and may include assignments, exercises, progress tests, oral and/or written examinations, etc.
  • Students may also select courses from the list of courses offered by other Departments of the University.

The full studies guide for the 2025 - 26 academic year can be found here.


Former Studies Guides can be found here.