Studies Program

BASIC REGULATIONS:

  1. The program is in accordance with the philosophy of the curricula of European Universities with which the Department cooperates, since it is based on the European Credit Transfer System (ECTS). The basis of this system is the Credit Unit (ECTS). Each course corresponds to a number of ECTS s referred in the program.

  2. To determine each course’s ECTS, the total demands of the course are taken into consideration (lectures, assignments, required preparation, etc)

  3. The student completes his/ her studies and is awarded a degree when he/ she has successfully attended courses corresponding to at least 240 ECTS’s. Credit is either through success in exams or by exemption, or by equivalence as an Erasmus course.

  4. According to the Department's indicative curriculum, each academic year includes educational activities corresponding to 60 academic ECTS’s.

  5. The program offers 14 compulsory courses.

  1. The program’s courses are divided into 2 basic categories:
    1. 14 compulsory courses which must be attended by all of the Department’s students
    2. Optional courses which are of two categories:
      • Courses offered by the Statistics Department
      • Courses offered by other Departments
  2. Compulsory courses are offered during the first 6 semesters (8 in the first year, 4 in the second year and 2 in the third year), so the student establishes the necessary background in order to make his following choices.
  3. In the last two semesters, no compulsory courses are offered. This way the student has the flexibility to form a studies program, which will cover the basic Statistics knowledge (as provided by the compulsory Statistics courses), while at the same time is given the chance to develop a program that meets his individual interests.
  4. During the first two semesters the student may enroll in lessons with a maximum of 30 ECTS.
  5. In the semesters from 3rd to 6th the student may enroll in lessons with a maximum of 38 ECTS per semester.
  6. In the 7th and 8th semesters the student may enroll in lessons with a maximum of 46 ECTS per semester.  There can be an excess only for the “Practical Training”.
  7. After the 4th year the student may enrol in lessons with a maximum of 46 ECTS per semester. There can be an excess only for the “Practical Training”.

In particular, the maximum ECTS’s per semesters are displayed in the table below:

Maximum ECTS’s

Year

Winter Semester

Spring Semester

1st’

30 ECTS

30 ECTS

2nd’

38 ECTS

38 ECTS

3rd’

38 ECTS

38 ECTS

4rth’

46 ECTS + Practical Training

46 ECTS + Practical Training

5th’ and above

46 ECTS + Practical Training

46 ECTS + Practical Training

  1. When the student chooses courses to attend each semester, the obligatory courses of previous semesters which the student has not passed and are offered in the specific semester must precede all other courses.
  2. There is the concept of prerequisite courses. Especially, “Estimation – Hypothesis Testing” of the 3rd semester is a prerequisite for “Linear Models” of the 4th Semester. “Linear Models” is a prerequisite for “Generalized Linear Models” of the 5th Semester as well as “Data Analysis” in the 6th Semester.
  3. Apart of the 14 compulsory courses that amount to 108 ECTS, the student must collect at least 72 ECTS from optional courses offered by the Statistics Department. The remaining 60 ECTS necessary for the degree can come either from optional courses offered by the Statistics Department, or by courses offered by other Departments in the University.  
  4. The table of the offered courses is announced each year and is depended on the availability of the corresponding teaching personnel. Some optional courses may not be offered if there is no available professor.
  5. By getting the degree, the student can obtain a computer certificate equivalent to ECDL in the public sector, if during his studies he successfully attended four of the following courses:

INFORMATICS KNOWLEDGE NECESSARY COURSES

Course Title

Department

INTRODUCTION TO PROGRAMMING WITH R

STAT

INTRODUCTION TO PROBABILITY AND STATISTICS WITH R

STAT

DATA ANALYSIS

STAT

SIMULATION

STAT

DATABASES

DET

COMMUNICATION NETWORKS

INF

COMPUTER NETWORKS

INF

DATABASE DESIGN

INF

  1. Students can enroll in the Teacher Education Program. More information can be found here:https://www.dept.aueb.gr/tep
  1. Lastly, the students are given the chance to attend one semester in a similar department in a University abroad through the ERASMUS+ program. The courses that are successfully completed by the student are corresponded to courses of the Department and are included in the student’s analytical total grade. For more information about student mobility you can visit this link: https://www.aueb.gr/el/content/πρόγραμμα-έρασμος.

PROGRAM STRUCTURE

Α’ Semester

Β’ Semester

  • Probability Ι (C)
  • Calculus Ι (C)
  • Linear Algebra Ι (C) 
  • Introduction to Programming with R (C)
  • Probability  ΙΙ (C)
  • Calculus ΙΙ (C)
  • Linear Algebra ΙΙ (C)
  • Introduction to Probability and Statistics with R (C)

C’ Semester

D’ Semester

  • Estimation and Hypothesis Testing (C)
  • Stochastic Processes Ι (C)
  • Introduction to Mathematical Analysis
  • Demographic Statistics
  • Introduction to Economic Theory
  • Introduction to Computerized Accounting and Finance
  • Linear Models (C)
  • Time Series Analysis (C)
  • Sampling
  • Mathematical Methods
  • Actuarial Science Ι

Ε’ Semester

F’ Semester

  • Generalized Linear Models (C)
  • Applied Linear Models
  • Bayesian Statistics
  • Statistical Quality Control
  • Theoretical Statistics
  • Introduction to Operations Research
  • Data Analysis (C)
  • Simulation
  • Multivariate Statistical Analysis
  • Biostatistics I
  • Probability Theory
  • Official Statistics

G’ Semester

Η’ Semester

  • Statistical Learning
  • Biostatistics ΙΙ
  • Econometrics
  • Stochastic Processes ΙΙ
  • Actuarial Science ΙΙ
  • Research Methodology*
  • Special Topics in Probability and Statistics 
  • Bachelor Thesis
  • Practical Training
  • Categorical Data Analysis
  • Advanced Sampling Methods
  • Statistical Methods for the Environment and Ecology
  • Numerical Methods in Statistics
  • Non Parametric Statistics
  • Bayesian Inference Methods
  • Special Topics in Probability and Statistics* Decision Theory
  • Bachelor Thesis
  • Practical Training

(C): compulsory courses

Notes:

  • Courses not offered on the academic year 2019-2020 are denoted with *.
  • Optional courses are offered only if there is an available instructor.
  • For all compulsory courses there are tutorials. Tutorial will also take place, according to availability, and to optional courses.
  • All courses are taught 4 hours weekly, plus 2 hours tutorials (where applicable)
  • Each course examination is determined by the instructor and may involve assignments, exercises, intermediate exams, etc.
  • The student can choose from a list of courses offered by other departments.

The full studies guide for the 2018-19 academic year can be found here.