040242 VO Econometrics and Statistics (MA) (2020W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften

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

Language: German

Examination dates

Tuesday 02.02.2021 16:45 - 18:15 Digital Tuesday 23.02.2021 16:45 - 18:15 Digital Monday 26.04.2021 16:45 - 18:15 Digital

Lecturers

Bertram Wassermann

Classes (iCal) - next class is marked with N

The course is carried out as a digital course. Slides and audios on the topics are published weekly. In addition, discussion and question forums are offered with the help of chats. The course the teacher can also be contacted directly and personally via email or video conference (by appointment).

    
    Tuesday
    06.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    13.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    20.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    27.10.
    13:15 - 14:45
    Digital
    
    Tuesday
    03.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    10.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    17.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    24.11.
    13:15 - 14:45
    Digital
    
    Tuesday
    01.12.
    13:15 - 14:45
    Digital
    
    Tuesday
    15.12.
    13:15 - 14:45
    Digital
    
    Tuesday
    12.01.
    13:15 - 14:45
    Digital
    
    Tuesday
    19.01.
    13:15 - 14:45
    Digital
    
    Tuesday
    26.01.
    13:15 - 14:45
    Digital

Information

Aims, contents and method of the course

Datamining and big data based on case studies

During the course we will learn and discuss concepts of data mining and big data using case studies.

The case studies will cover areas such as

. Customer Relationship Management
. Fraud Detection
. Revenue Management
. Market Research

The presented concepts of data-naming and big data will include i.a.

. Sampling
. Supervised und unsupervised learning
. Multiple Regression,
. Logistic Regression
. Statistical Analysis of Frequency Data
. Analysis of variance
. Time series analysis

Assessment and permitted materials

Final test at the end of the course, Written Exam

If possible, the test is carried out as a face-to-face test personally at the University campus

Minimum requirements and assessment criteria

To pass this course you have to attain min 60% of the total points.

Examination topics

1) Analyze a given Problem and sketch a solution with Datamining methods
2) Describe the steps of a standard analysis
3) Understand (= be able to read and Interpret) statistical model equations
and statistical Reports

More Details about the exam will be given during the course.
Analyze a given Problem and sketch a solution with Datamining methods

Understand (= be able to read and Interpret) statistical model equations
and Datamining concepts

More Details about the exam will be given during the course.

Reading list

Werner Brannath, Andreas Futschik, Statistik für Wirtschaftswissenschaftler

Weitere Literatur wird während der Vorlesung bekannt gegeben.

Folien, die im Kurs diskutiert werden (werden auf der Homepage veröffentlicht).

Association in the course directory

Last modified: Fr 12.05.2023 00:12