Universität Wien
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040971 UK Computational Statistics (2021S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
REMOTE
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. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 01.03. 18:30 - 20:00 Digital
  • Monday 08.03. 18:30 - 20:00 Digital
  • Monday 15.03. 18:30 - 20:00 Digital
  • Monday 22.03. 18:30 - 20:00 Digital
  • Monday 12.04. 18:30 - 20:00 Digital
  • Monday 19.04. 18:30 - 20:00 Digital
  • Monday 26.04. 18:30 - 20:00 Digital
  • Monday 03.05. 18:30 - 20:00 Digital
  • Monday 10.05. 18:30 - 20:00 Digital
  • Monday 17.05. 18:30 - 20:00 Digital
  • Monday 31.05. 18:30 - 20:00 Digital
  • Monday 07.06. 18:30 - 20:00 Digital
  • Monday 14.06. 18:30 - 20:00 Digital
  • Monday 21.06. 18:30 - 20:00 Digital
  • Monday 28.06. 18:30 - 20:00 Digital

Information

Aims, contents and method of the course

Objectives:

In this course, students will
- use R for data visualisation and analysis
- draft detailed problem reports
- understand the underlying methods
- tailor R-solutions to specific needs
- learn fundamental concepts in statistical computing

Contents:

1. Data Processing
2. Hypothesis Testing
3. Regression Analysis
4. Survival Analysis
5. Parameter Estimation
6. Dimension Reduction
7. Simulation

Methods:

Completely online via Moodle.
Students will participate in coding with R.

Assessment and permitted materials

Submit three detailed problem reports.

Minimum requirements and assessment criteria

Each report contributes a third to the final grade.
To pass, half of the total points have to be earned.

Examination topics

Contents of the topics covered.

Reading list

Robert, C. And Casella, G. (2004): Monte Carlo Statistical Methods

Association in the course directory

Last modified: Fr 12.05.2023 00:13