Universität Wien
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053614 VU Statistics for Data Science (2024W)

6.00 ECTS (4.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work
Moodle

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

  • Thursday 03.10. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 07.10. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 10.10. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 14.10. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 17.10. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Monday 21.10. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 24.10. 09:45 - 11:15 Seminarraum 3, Währinger Straße 29 1.UG
  • Monday 28.10. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 31.10. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Monday 04.11. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 07.11. 09:45 - 11:15 Seminarraum 2, Währinger Straße 29 1.UG
  • Monday 11.11. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 14.11. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Monday 18.11. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 21.11. 09:45 - 11:15 PC-Unterrichtsraum 3, Währinger Straße 29 1.OG
  • Monday 25.11. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 28.11. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Monday 02.12. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 05.12. 09:45 - 11:15 Seminarraum 3, Währinger Straße 29 1.UG
  • Monday 09.12. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 12.12. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Monday 16.12. 11:30 - 13:00 Seminarraum 9, Währinger Straße 29 2.OG
  • Thursday 09.01. 09:45 - 11:15 Seminarraum 3, Währinger Straße 29 1.UG
  • Monday 13.01. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 16.01. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Monday 20.01. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 23.01. 09:45 - 11:15 Seminarraum 3, Währinger Straße 29 1.UG
  • Monday 27.01. 11:30 - 13:00 Seminarraum 10, Währinger Straße 29 2.OG
  • Thursday 30.01. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG

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
- MC and Bayes methods
- Bootstrap and Jackknife
- Linear Models and Model Selection
- Statistical Network Analysis
- 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 sessions.
At the end of the semester there will be a written final exam.

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.

Attandence of the very first session is mandatory and being absent leads to deregistration for the benefit of people on the waiting list.

Examination topics

Content of the lectures and homework exercises.

Reading list

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

Association in the course directory

Modul: SDS

Last modified: Th 03.10.2024 12:45