In case of limited activity on campus the course will take place via Hybrid Mode.
The course will be held in presence for a part of the participants. At the same time, the course is streamed for all students who cannot be on campus. In case the number of students who are eligible and willing to come to the class is more than the number of Covid-19 seats available in the room, we will apply certain rotation rules. Under special circumstances (travel restrictions, health issues) it is also possible for students to participate in the course purely remotely. More detailed information on who is in which group will be communicated before the start of the lecture via Learn or email.
Under the synchronous hybrid mode, there will be in-class teaching together with synchronous streaming. For the remotely-attending group there will be an opportunity to ask questions during the lecture through MS Teams. Moreover, we encourage the active use of the Forum page at Learn. The weekly tutorials will continue to take place online via MS Teams.
Students are expected to be active in the class (or online) as well as on the Forum page of the course. Moreover, students will take part in a group work while working on the homework assignments.
Attendance is still mandatory both online and on campus and can only be suspended or converted to pure online attendance for a valid reason.
The assessment is based on an in-class midterm (40%), homework assignments (group work) (20%) and an in-class final exam (40%).
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.
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 of at least 80% of the classes is necessary to fulfill the requirements.
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)
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.