364-1105-00L  Bayesian Data Science

SemesterAutumn Semester 2019
LecturersS. Feuerriegel
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
364-1105-00 GBayesian Data Science
Exclusively for PhD studies
6s hrs
25.09.10:15-17:00WEV F 109 »
S. Feuerriegel

Catalogue data

AbstractThis course introduces to the Bayesian approach to statistical modeling and further covers on how to formulate and evaluate Bayesian models.
Learning objectiveStudents will gain the ability to
- understand the difference between frequentist statistics and Bayesian approaches
- formalize and implement Bayesian models in R/Stan.
- evaluate estimated models.
LiteratureStudents are asked to prepare Chapters 2 and 3 of the following book prior to the first course data:
Richard McElreath (2016). Statstical Rethinking: A Bayesian Course with Examples in R and Stan. CRC Press.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits1 credit
ExaminersS. Feuerriegel
Typeungraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Doctoral Department of Management, Technology, and EconomicsDoctoral Studies in ManagementWInformation