Market Research & Methods
level of course unit
1st Master cycle
Learning outcomes of course unit
The participants:
• know qualitative and quantitative methods of analysis
• know the design aspects of questionnaires: Question types, scale levels, alignment and dimensionality
• can evaluate questionnaires and analyze and interpret them using descriptive and simple inferential statistics: Data collection, processing and evaluation
• can develop and formulate research questions and create and process research hypotheses
• can create and send an online questionnaire and collect and evaluate the data accordingly
• can apply inferential statistical evaluation procedures (e.g. in SPSS, Jasp, Datatab, Excel etc.)
• can create an interview guideline, conduct and evaluate expert interviews
• can conduct a qualitative content analysis
• can perform and interpret descriptive analyses and inferential statistical tests to describe data, test hypotheses and draw generalizable conclusions
• can select, apply and critically evaluate various AI-supported tools for data analysis and visualization
• can adapt their research results to different target groups and communicate them effectively
• can explain and apply the ethical principles of research with regard to data protection, anonymity and informed consent
prerequisites and co-requisites
Academic Methods
course contents
• Secondary, qualitative, quantitative research
• Questionnaire development and design
• Data modeling, coding and test procedure selection
• Introduction to online questionnaire design: Question variants, dynamic content, sending and evaluating responses
• Selected descriptive indicators, extension by inferential statistical methods
• Procedure and execution of interviews, transcription, coding of texts (category formation and generalization)
• The content-analytical procedure model (qualitative content analysis)
• Basics of data analysis: descriptive statistics and inferential statistics
• Use of AI-supported tools for research and data visualization
• Presentation and communication of research results
• Ethics in research: data protection, anonymity, informed consent
recommended or required reading
• Magerhans, A. (2016): Marktforschung, Eine praxisorientierte Einführung
• Kuß, A./ Wildner, R./ Kreis, H. (2014): Marktforschung, Grundlagen der Datenerhebung und Datenanalyse
• Koch, J./ Gebhardt, P. (2016): Marktforschung: Grundlagen und praktische Anwendungen
• Theobald, A. (2017): Praxis Online-Marktforschung, Grundlagen - Anwendungsbereiche - Durchführung
• Porst, R. (2014): Fragebogen, Ein Arbeitsbuch
• Kaiser, R. (2014): Qualitative Experteninterviews, Konzeptionelle Grundlagen und praktische Durchführung
• Mayring, P. (2015): Qualitative Inhaltsanalyse: Grundlagen und Techniken
• Cleff, T. (2015): Deskriptive Statistik und Explorative Datenanalyse
• Duller, C. (2013): Einführung in die Statistik mit EXCEL und SPSS, 3. Aufl.
assessment methods and criteria
Projektarbeit
language of instruction
German
number of ECTS credits allocated
6
eLearning quota in percent
35
course-hours-per-week (chw)
3
planned learning activities and teaching methods
ILV (Blended Learning, Inverted Classroom)
semester/trimester when the course unit is delivered
2
name of lecturer(s)
n.N.
year of study
1
recommended optional program components
none
course unit code
6_MFM
type of course unit
integrated lecture
mode of delivery
Compulsory
work placement(s)
no