Universität Wien

053614 VU Statistics for Data Science (2023W)

Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 02.10. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 05.10. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 09.10. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 12.10. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 16.10. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 19.10. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 23.10. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Monday 30.10. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Monday 06.11. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 09.11. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 13.11. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 16.11. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 20.11. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 23.11. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 27.11. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 30.11. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 04.12. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 07.12. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 11.12. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 14.12. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 08.01. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 11.01. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 15.01. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 18.01. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 22.01. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG
  • Thursday 25.01. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 29.01. 11:30 - 13:00 Seminarraum 4, Währinger Straße 29 1.UG

Information

Aims, contents and method of the course

The goal of the course is to establish a thorough understanding of basic concepts and methods of statistical inference in the context of modern data science.

We will cover the following topics:
- Principles of statistical modeling and inference
- Simulation and Bootstrap methods
- Linear Models and High-dimensional data
- Statistical inference for network data
- Differential Privacy

This course is divided into lectures and lab/homework sessions.

Assessment and permitted materials

Students have to solve homework problems and present their results in the lab session.
At the end of the semester students can choose the format of their final exam: a) oral final exam or b) take-home project.
In case a) you get 30 minutes of general questions about the course material. In case b) you have to do a 15 minutes discussion of your solutions with the lecturer.

Minimum requirements and assessment criteria

Homework 60%
Final Exam 40%

At least half of the homework problems have to be solved in order to get a passing grade.

Examination topics

Option a)
The final exam will cover all the material that was discussed in lectures and homework sessions during the semester.

Option b)
The final project will require you to independently solve theoretical and applied statistics problems related to what we have learned in the course.

Reading list

Rice, J.A. (2007): “Mathematical Statistics and Data Analysis”, Duxbury.

Association in the course directory

Modul: SDS

Last modified: Su 01.10.2023 12:27