Computerlab - Applied Econometrics (10162000)
Dr. Tamara Schamberger
Offered in: summer term (in English) and in winter term (in German)
time: Monday, 10:00 - 14:00 (SR 409)
In the summer semester 2023, the course will be offered as a 4-hour course from 17.04.2023 to 05.06.2023. The written exam will already take place on 12.06.2023. Please note that there will be no further exam in July/August 2023.
The aim of the lecture is to teach you the basic methods and concepts of statistical inference (e.g., hypothesis testing and regression analysis) their practical application and their correct interpretation. Mathematics, is used throughout the course, however we will not dwell deep into mathematical subtleties but solely (ab)use mathematics as an efficient and unambiguous way of communicating. The focus is on the development of an intuitive understanding of the topics discussed in class while sensitizing you for “real” problems of statistical inference (with particular focus on regression analysis).
Principally, attendance of your introductory statistics courses “Grundlagen der Statistik” and “Grundlagen der QWF” are not required, however, a basic understanding of statistics and statistical methodology will be vital in order to follow the course.
Who is the course for?
As lecturer I strongly recommend the course to anyone planning to write any kind of empirical Bachelorthesis (at our chair or at any other chair). Moreover, anyone interested in applied statistics will probably find what she or he is looking for.
The examination is a 60-minute paper-based written exam. As an aid, students may use their own laptop using the Excel and Gretl software used in the course to the exclusion of communication options.
For ERASMUS students: Registration to exam online per WueStudy
Sanderring 2, Room 290
Please visit WueCampus and WueStudy for further information.
Data analysis (Praxis der Datenanalyse (Ausgewählte Probleme aus dem Bereich Methoden) 10168000)
Dr. Lukas Kagerbauer
Offered in: summer term
Concept and content
Business, science, institutions and politics - The daily work in all areas of the economy is based on the collection, processing and analysis of different types of data. First data must be collected or even generated. However, data acquisition is only one part. The second part is modifying, processing and finally interpreting the data with the help of various software solutions with the help of appropriate methods. Prerequisite for this is theoretical and practical knowledge of how to work with different statistical programs (such as the free software R) and with different techniques of data preparation and filtering. The course is aimed at bachelor students of Wirtschaftswissenschaften as well as bachelor students of other fields (including business informatics) with economic relevance.
The cours basically deals with the following questions:
- Where can regional and national economic data for research, presentations and projects be found?
- How do different data types and indicators differ from each other?
- Which methods and filter procedures must be used before the data can be interpreted?
- Which software solutions can be used? Are there more possibilities than Excel? Advantages of the practical work with the free statistical software R
This lecture is a core elective which can be integrated in the bachelor programme "Wirtschaftswissenschaft" as "Ausgewählte Probleme aus dem Bereich Methoden" and in the bachelor programme "Wirtschaftsmathematik" as "Ausgewählte Probleme der Wirtschaftswissenschaft".
Outline and procedure
The course is essentially divided into three parts: Theory, technical application and practice.
- In the first part of the course, the previously mentioned questions are discussed theoretically.
- In the second part basic knowledge in the technical handling of various statistical databases (Destatis, Genesis, Eurostat, DaReZa, Agentur für Arbeit etc.) and the statistical software R are conveyed.
- In addition to the classes excursions to regional companies, institutions and research institutes take place. There may be an opportunity to present and discuss a previously in developed topic
For further information see WueStudy and WueCampus.