0665 Quantitative and Qualitative Methods II
PD Mag.Dr. Barbara Haas, Assoz.Prof PD Dr. Astrid Pennerstorfer
Weekly hours
Language of instruction
09/01/23 to 09/30/23
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Day Date Time Room
Monday 10/02/23 02:00 PM - 05:00 PM D4.0.047
Wednesday 10/04/23 02:00 PM - 04:00 PM LC.2.064 PC Raum
Monday 10/09/23 02:00 PM - 04:00 PM D2.0.330
Wednesday 10/11/23 02:00 PM - 05:00 PM LC.2.064 PC Raum
Monday 10/16/23 02:00 PM - 04:00 PM D2.0.330
Wednesday 10/18/23 02:00 PM - 04:00 PM D2.0.330
Monday 10/23/23 02:00 PM - 04:00 PM D2.0.330
Monday 11/06/23 02:00 PM - 06:00 PM D4.3.213
Monday 11/13/23 02:00 PM - 04:00 PM D2.0.330
Wednesday 11/15/23 02:00 PM - 04:00 PM D5.1.003
Monday 11/20/23 02:00 PM - 04:00 PM D2.-1.019 Workstation-Raum
Wednesday 11/22/23 02:00 PM - 04:00 PM D3.0.237
Monday 11/27/23 02:00 PM - 04:00 PM D3.0.237
Wednesday 11/29/23 02:00 PM - 04:00 PM LC.2.064 PC Raum
Wednesday 12/06/23 02:00 PM - 04:00 PM D2.0.330
Wednesday 12/13/23 02:00 PM - 04:00 PM LC.-1.038
Monday 12/18/23 02:00 PM - 04:00 PM D2.0.330
Monday 01/08/24 02:00 PM - 04:00 PM TC.-1.61
Wednesday 01/10/24 02:00 PM - 03:00 PM D2.0.330
Wednesday 01/17/24 02:00 PM - 06:00 PM D2.0.330

There is still an ongoing debate on whether quantitative and/or qualitative methods are more appropriate to answer different research questions. Yet, both methodological approaches offer valuable contributions depending on the aim of research. While qualitative studies are suited for theory creation and require primarily exploratory designs (constructivist or phenomenological approaches), quantitative research seeks to test theories by quantifying structured data (statistical analysis). The course covers special topics in both qualitative and quantitative methods.

This semester students will work in small research groups, dealing with a specific topic. The groups learn how to do research in a team. They will draft a research design, formulate empirical questions, present them in class and they will gain relevant insights from the feedback of others. In the final research report, the quantitative and qualitative results should be connected to each other, placing a focus on the main (methodological) insights.  

In the qualitative part the aim is to develop mixed methods research designs which fit to the topics and questions of the students’ projects. With a special focus on the premises and basic ideas of empirical research, we look at ways of how these are implemented adequately in the designs. Furthermore, this part will focus on the qualitative method of expert interviews. Students will generate and analyse qualitative data.

In the quantitative part of the course, students work on their research project, using large quantitative data sets and applying regression-based methods.

Learning outcomes

After successful completion of this course, students will be able to:

- develop a research question (based on the state of the art and on theories)

- specify a mixed methods research strategy in more depth (empirical design) and to formulate quantitative hypotheses

- to apply suitable methods: to analyse data using econometric techniques: regression analysis, discrete and multilevel models, and to conduct qualitative expert interviews

- to analyse, interpret and try to link the varying results from quantitative and qualitative methods

- to present research results (including a quality assessment)

- to write an academic article

Students are expected to:

- prepare the literature for discussions in class

- actively participate in discussions and assignments in class

- submit a research design

- to select data

- to apply methods

- to analyse and interpret data

- to submit a research article

Attendance requirements

80% attendance of the class is required! If you miss a class, please inform us in advance!



Teaching/learning method(s)

Design of Teaching

drafting and applying a research design, presentation, discussion, readings followed by aquestion-answer session to the obligatory texts and practical exercises.


Active participation in class, group assignments, presentation in class, final seminar paper on own project


- individual tasks (assignments): 20%

- contributions in class: 5%

- Group tasks: 75%

SEEP courses do not allow creation of assignments, exam answers or other assessed work using generative AI (e.g. ChatGPT).  All such work is expected to be the original work by the student concerned and is assessed as such.  Work copied from a generative AI source is equivalent to plagiarism and will be treated as such.

Prerequisites for participation and waiting lists
Quantitative and Qualitative Methods I

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Last edited: 2023-09-27