Universität Wien

040021 UK Python/SAS (2018S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
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

max. 50 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Wednesday 07.03. 16:45 - 20:00 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 14.03. 16:45 - 20:00 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 19.03. 16:45 - 20:00 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 02.05. 16:45 - 20:00 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 23.05. 16:45 - 20:00 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 06.06. 16:45 - 20:00 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 13.06. 16:45 - 20:00 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Wednesday 20.06. 16:45 - 20:00 Hörsaal 2 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

The course aims at providing experience with the application of selected statistical analysis methods. Students will participate in real life consulting sessions and perform data analysis within current projects. Further insight in analysis methods and reporting of results will be gained through presentations of selected scientific publications.

Assessment and permitted materials

Grading is based on three components: 1) Written summary of the problems and proposed solutions encountered in the consulting sessions, 2) Written report of the performed data analysis, 3) Presentation concerning the statistical problems and methods found in a selected scientific publication.

Minimum requirements and assessment criteria

The three components are first graded separately and the scores are then combined using weights part 1: 30%, part 2: 50%, part 3: 20%. The final grade depends on the overall score G: G<=50% Nicht Genügend, 50%87,5% Sehr Gut.

Examination topics

Wird in der LV detailliert besprochen (Ausarbeiten von Beispielen)

Reading list

SAS-Links: http://www.sascommunity.org/wiki/Austria_--_SAS_Club#News_und_Links

Download-Seiten für die Programme aus den Büchern:

Applying Data Science: http://www.sascommunity.org/wiki/DOWNLOAD_SECTION:_Applying_Data_Science_-_Business_Case_Studies_Using_SAS
Data Quality for Analytics: http://www.sascommunity.org/wiki/Data_Quality_for_Analytics_--_Download_Page
Data Preparation for Analytics: http://www.sascommunity.org/wiki/Data_Preparation_for_Analytics

Association in the course directory

Last modified: Mo 07.09.2020 15:28