Syllabus

Titel
1751 Empirical Research and Analysis I
LV-Leiter/innen
Mag. Marianne Stephanides, B.Sc.
Kontakt
  • LV-Typ
    PI
  • Semesterstunden
    2
  • Unterrichtssprache
    Englisch
Anmeldung
19.09.2019 bis 22.09.2019
Anmeldung über LPIS
Hinweise zur LV
Planpunkt(e) Bachelor
Termine
Wochentag Datum Uhrzeit Raum
Donnerstag 03.10.2019 10:30 - 13:30 D5.0.002
Donnerstag 10.10.2019 10:30 - 13:30 D5.0.002
Donnerstag 10.10.2019 10:30 - 13:30 TC.3.02
Donnerstag 17.10.2019 10:30 - 13:30 D5.0.002
Donnerstag 24.10.2019 10:30 - 13:30 D5.0.002
Donnerstag 31.10.2019 10:30 - 13:30 D5.0.002
Donnerstag 07.11.2019 10:30 - 13:30 D5.0.002
Donnerstag 14.11.2019 10:30 - 13:30 TC.3.10
Donnerstag 21.11.2019 10:30 - 12:30 TC.3.05

Inhalte der LV

Data analysis is the basis of any evidence-based managerial decision making. This course teaches students about selected methods of data creation, collection, and analysis. It draws on econometrics and statistical methods developed to estimate economic relationships, testing theories about real-world behaviour, and evaluating business and public policies.

In particular, this course will provide a review of basic statistical tools, introduce students to regression analysis including linear regression with multiple regressors, non-linear regression models, dummy variables, and longitudinal or panel data methods. The course will be application based and will also cover survey and questionnaire design.

A number of academic research papers will also be discussed to illustrate the main concepts.

To link the statistical and econometric concepts to practical examples, students will be shown how to manage and analyse data during class using the statistical software package STATA.

Lernergebnisse (Learning Outcomes)

On successful completion of the course, you should:

  • understand the concept of evidence-based decision-making;
  • be able to choose the right method of statistical data analysis to answer a research question;
  • have a good understanding of the discussed methods as well as their limitations;
  • understand the difference between causality and correlation;
  • be able to present and discuss findings from your research;
  • perform simple analysis with STATA;

Regelung zur Anwesenheit

In order to learn the content properly, students need to be present in each lecture. 

Many relevant concepts, examples and applications will be discussed which may not be included on the lecture slides.

Lehr-/Lerndesign

After a short introduction and recap, the course will focus on specific problem-based examples and case studies. Each broader topic/method is organised in 2 classes.

Typically, in the first class we will start with examples for related business/strategy-related research questions, and discuss how to find and/or generate data to answer these questions. This is followed by an introduction of the respective analysis method. In in-class tasks and homework assignments, students are asked to try out data generation and analysis themselves, with data provided to them. The second meeting then usually discusses specific analysis concepts related to the case, and includes practical work with STATA as well as more examples for applications of the method.

Since all empirical applications will involve the use of the statistical software STATA, you are strongly encouraged to use STATA. 

STATA is freely available on university lab computers, or alternatively you can purchase a single-user student license.

Leistung(en) für eine Beurteilung

Participation (10%)

Problem sets (20%)

Empirical survey study (20%)

Final exam (50%)

Zuletzt bearbeitet: 26.08.2019



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