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. To obtain the degree of the Department, the student must acquire a total of 240 ECTS’s. All of the program’s courses account for 8 ECTS and the lectures are 4 hours per week. (the lesson Introduction to Computerized Accounting and Finance is excluded, as it accounts for 6 ECTS and is offered from the department of Accounting and Finance).
  4. The program offers 14 compulsory courses.

COURSES CATEGORIES

  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 32 ECTS.
  5. In the remaining semesters (3rd to 8th) the student may enroll in lessons with a maximum of 40 ECTS per semester. For the last two semesters there can be an excess only for the “Practical Training”.
  6. After the 4th year the student may enrol in lessons with a maximum of 48 ECTS per semester.
  7. 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.
  8. 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.
  9. Apart of the 14 compulsory courses that amount to 112 ECTS, the student must collect at least 72 ECTS from optional courses offered by the Statistics Department. The remaining 56 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.  
  10. 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.
  11. 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:
  12. 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

  13. 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 matched to courses of the Department and are included in the student’s analytical total grade.

NEW 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
  • Data Analysis (C)
  • Simulation
  • Multivariate Statistical Analysis
  • Biostatistics I
  • Probability Theory

G’ Semester

Η’ Semester

  • Statistical Learning
  • Biostatistics ΙΙ
  • Econometrics
  • Introduction to Operational Research
  • 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
  • Official Statistics
  • Bayesian Inference Methods
  • Special Topics in Probability and Statistics
  • Bachelor Thesis
  • Practical Training

NOTE: Courses not offered on the academic year 2018-2019 are noted with *.

Transitional provisions for older students are here.

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