1303 Probability and Statistics (Science Track)
Dr. Sühan Altay
Weekly hours
Language of instruction
10/04/23 to 10/04/23
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Day Date Time Room
Tuesday 10/10/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 10/17/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 10/24/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 10/24/23 04:00 PM - 05:30 PM TC.3.11
Tuesday 10/31/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 11/07/23 01:00 PM - 03:30 PM TC.5.03
Tuesday 11/14/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 11/21/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 11/28/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 12/05/23 01:00 PM - 03:30 PM TC.5.02
Tuesday 12/05/23 05:00 PM - 07:00 PM TC.3.08
Wednesday 12/06/23 05:00 PM - 07:00 PM TC.4.15
Tuesday 12/12/23 01:00 PM - 03:30 PM EA.6.026

This course is a graduate course intended for Economics Masters students. The course aims at building theoretical statistics starting from the basics of probability theory. In particular, the purpose of this course is to give further knowledge in statistics and probability theory which is essential for econometrics and statistical modeling.

Learning outcomes

After completing this class successfully the student will have the ability to:

  • define, describe and work with the basic concepts in probability and statistics,
  • use methods and ideas from probability and statistics to solve scientific problems,
  • solve practical problems and interpret the results.

Attendance requirements

Attendance of at least 80% of the classes is necessary to fulfill the requirements.

Teaching/learning method(s)

The course consists of lectures, accompanying homework assignments and one midterm and the final examinations. The lecture part presents the theoretical concepts. There will be 4 homework assignments related to the subjects covered during the lecture. Students are allowed to hand in the assignments as a group of at most three people.

In order to provide students with the necessary support, weekly tutorials will be offered by a tutor.


  • 20 % Homework assignments
  • 40 % Midterm Exam
  • 40 % Final Exam

The following grading scale applies:

    90.00-100.00 - Excellent (1)
    77.00-89.00 - Good (2)
    64.00-76.00 - Satisfactory (3)
    51.00-63.00 -  Sufficient (4)
      0.00-50.00 -  Insufficient (5)

Prerequisites for participation and waiting lists

Familiarity with mathematical concepts such as basic set theory, convergence of sequences and functions, continuity, linear maps and matrices, definite and indefinite integral, differentiation, and Taylor polynomial series is expected. Knowledge in basic probability theory and statistics is desirable.


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Availability of lecturer(s)

Unit details
Unit Date Contents

Basics of probability theory


Conditional probability and independence; Random variables


Distribution functions; Density and mass fuctions


Transformations of random variables , Expectation,  Moments and moment generating functions.


Discrete distributions; Continuous distributions


Midterm Exam


Multivariate distributions, joint and marginal distributions.  


Conditional Distributions and Expectations. Independent random variables. Covariance and correlation


Probability Inequalities; Numerical Inequalities; Functional Inequalities


Convergence concepts; Law of large numbers, Central limit theorem.


Final Exam


Last edited: 2023-10-03