Modul
Statistics and Econometrics [M-WIWI-101599]
Credits
9Recurrence
Jedes SemesterDuration
1 SemesterLanguage
GermanLevel
3Version
6Responsible
Organisation
- KIT-Fakultät für Wirtschaftswissenschaften
Part of
Bricks
Identifier | Name | LP |
---|---|---|
T-WIWI-106623 | Technical Conditions Met | 0 |
T-WIWI-103066 | Data Mining and Applications | 4.5 |
T-WIWI-102736 | Economics III: Introduction in Econometrics | 5 |
T-WIWI-103063 | Analysis of Multivariate Data | 4.5 |
T-WIWI-103065 | Statistical Modeling of Generalized Regression Models | 4.5 |
T-WIWI-110939 | Financial Econometrics II | 4.5 |
T-WIWI-112153 | Microeconometrics | 4.5 |
T-WIWI-103064 | Financial Econometrics | 4.5 |
Competence Certificate
The assessment is carried out as partial written exams (according to Section 4(2), 1 of the examination regulation) of the single courses of this module, whose sum of credits must meet the minimum requirement of credits of this module. The examinations are offered every semester. Re-examinations are offered at every ordinary examination date. The assessment procedures are described for each course of the module seperately.
The overall grade of the module is the average of the grades for each course weighted by the credits and truncated after the first decimal.
Competence Goal
The student
- shows an advanced understanding of Econometric techniques and statistical model building.
- is able to develop Econometric models for applied problems based on available data
- is able to apply techniques and models with statistical software, to interpret results and to judge on different approaches with appropriate statistical criteria.
Prerequisites
The course "Economics III: Introduction in Econometrics“ is compulsory and must be examined. In case the course „Economics III: Introduction in Econometrics“ has already been examined within the module „Applied Microeconomics“, the course „Economics III: Introduction in Econometrics“ is not compulsory.
Content
The courses provide a solid Econometric and statistical foundation of techiques necessary to conduct valid regression, time series and multivariate analysis.
Workload
The total workload for this module is approximately 270 hours.