314004 Reading Course "Statistische Wissenschaften" (S) (SoSe 2022)
Contents, comment
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In this course we address causal inference and generalized linear multilevel models from a simple Bayesian perspective. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models.
Requirements for participation, required level
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It is expected that participants are familiar with basic statistics (e.g. regression).
Bibliography
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McElreath, Richard. Statistical rethinking: A Bayesian course with examples in R and Stan. Chapman and Hall/CRC, 2020.
Teaching staff
Dates ( Calendar view )
| Frequency | Weekday | Time | Format / Place | Period |
|---|
Subject assignments
| Module | Course | Requirements | |
|---|---|---|---|
| 31-SW-AKStat Ausgewählte Kapitel der Statistik | Veranstaltung aus dem Bereich Statistik oder einem methodisch verbundenen Gebiet 4 LP | Graded examination
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Student information |
| Veranstaltung aus dem Bereich Statistik oder einem methodisch verbundenen Gebiet 4 LP | Graded examination
|
Student information | |
| 31-SW-StaFo Forschung in der Statistik | Reading Course | Graded examination
|
Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
| Degree programme/academic programme | Validity | Variant | Subdivision | Status | Semester | LP | |
|---|---|---|---|---|---|---|---|
| Economics and Management (BiGSEM) / Promotion | Economics; Prerequisites | 4 |
E-Learning Space
A corresponding course offer for this course already exists in the e-learning system. Teaching staff can store materials relating to teaching courses there:
- Registered number: 7
- This is the number of students having stored the course in their timetable. In brackets, you see the number of users registered via guest accounts.
- eKVV participant management:
- eKVV participant management is used for this course.
- Show details
- Address:
- SS2022_314004@ekvv.uni-bielefeld.de
- This address can be used by teaching staff, their secretary's offices as well as the individuals in charge of course data maintenance to send emails to the course participants. IMPORTANT: All sent emails must be activated. Wait for the activation email and follow the instructions given there.
- If the reference number is used for several courses in the course of the semester, use the following alternative address to reach the participants of exactly this: VST_321828082@ekvv.uni-bielefeld.de
- Coverage:
- 6 Students to be reached directly via email
- Notes:
- Additional notes on the electronic mailing lists
- Last update basic details/teaching staff:
- Tuesday, April 12, 2022
- Last update times:
- Friday, April 22, 2022
- Last update rooms:
- Friday, April 22, 2022
- Type(s) / SWS (hours per week per semester)
- S / 2
- Language
- This lecture is taught in english
- Department
- Faculty of Business Administration and Economics
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- Questions or correction requests for this course?
- Planning support
- Clashing dates for this course
- Links to this course
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- https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=321828082
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- ID
- 321828082