040971 UK Computational Statistics (2022S)
Continuous assessment of course work
Labels
REMOTE
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).
- Registration is open from Mo 07.02.2022 09:00 to Mo 21.02.2022 12:00
- Registration is open from Th 24.02.2022 09:00 to Fr 25.02.2022 12:00
- Deregistration possible until Mo 14.03.2022 23:59
Details
max. 65 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Monday 07.03. 15:00 - 16:30 Digital
- Monday 07.03. 18:30 - 20:00 Digital
- Monday 14.03. 15:00 - 16:30 Digital
- Monday 14.03. 18:30 - 20:00 Digital
- Monday 21.03. 15:00 - 16:30 Digital
- Monday 21.03. 18:30 - 20:00 Digital
- Monday 28.03. 15:00 - 16:30 Digital
- Monday 28.03. 18:30 - 20:00 Digital
- Monday 04.04. 15:00 - 16:30 Digital
- Monday 04.04. 18:30 - 20:00 Digital
- Monday 25.04. 15:00 - 16:30 Digital
- Monday 25.04. 18:30 - 20:00 Digital
- Monday 02.05. 15:00 - 16:30 Digital
- Monday 02.05. 18:30 - 20:00 Digital
- Monday 09.05. 15:00 - 16:30 Digital
- Monday 09.05. 18:30 - 20:00 Digital
- Monday 16.05. 15:00 - 16:30 Digital
- Monday 16.05. 18:30 - 20:00 Digital
- Monday 23.05. 15:00 - 16:30 Digital
- Monday 23.05. 18:30 - 20:00 Digital
- Monday 30.05. 15:00 - 16:30 Digital
- Monday 30.05. 18:30 - 20:00 Digital
- Monday 13.06. 15:00 - 16:30 Digital
- Monday 13.06. 18:30 - 20:00 Digital
- Monday 20.06. 15:00 - 16:30 Digital
- Monday 20.06. 18:30 - 20:00 Digital
- Monday 27.06. 15:00 - 16:30 Digital
- Monday 27.06. 18:30 - 20:00 Digital
Information
Aims, contents and method of the course
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.
To pass, half of the total points have to be earned.
Examination topics
Contents of the topics covered.
Reading list
Lecture notes.
Association in the course directory
Last modified: Th 11.05.2023 11:27
- get acquainted with code documentation
- 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 computingContents:1. Intro to R
2. Data Processing
3. Hypothesis Testing
4. Regression Analysis
5. Dimension Reduction
6. Simulation
7. Model SelectionMethods:Completely online via Moodle.
Students will participate in coding with R.