ESF:MPH_EVPP Empirical research - Course Information
MPH_EVPP Empirical research for business practice
Faculty of Economics and AdministrationSpring 2025
- Extent and Intensity
- 1/2/0. 6 credit(s). Type of Completion: zk (examination).
In-person direct teaching - Teacher(s)
- doc. Ing. Ondřej Částek, Ph.D. (lecturer)
Ing. Renata Čuhlová, Ph.D., BA (Hons) (lecturer)
Mgr. Laura Fónadová, Ph.D. (lecturer)
doc. Ing. Radoslav Škapa, Ph.D. (lecturer)
doc. Ing. Ondřej Částek, Ph.D. (seminar tutor)
Ing. Renata Čuhlová, Ph.D., BA (Hons) (seminar tutor)
Mgr. Laura Fónadová, Ph.D. (seminar tutor)
doc. Ing. Radoslav Škapa, Ph.D. (seminar tutor) - Guaranteed by
- doc. Ing. Ondřej Částek, Ph.D.
Department of Business Management – Faculty of Economics and Administration
Contact Person: Vlasta Radová
Supplier department: Department of Business Management – Faculty of Economics and Administration - Prerequisites
- (! MPH_MVPS Marketing Research &&!NOWANY( MPH_MVPS Marketing Research ))
The pre-requisite is knowledge of basic statistics. This course, therefore, deepens this knowledge and adds specifics of data typically used by managers and marketers. - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Business Management (programme ESF, N-PEM)
- Business Informatics (programme ESF, N-PEM)
- Course objectives
- This course introduces business research methods and research process. Specifically, its aim is to develop students’ knowledge and ability to independently design and perform (mainly) quantitative research and to apply selected statistical analysis on data typical for the management and marketing field.
- Learning outcomes
- The student will be, after successfully finishing the course, capable of:
- formulating goals, research questions and their operationalization into hypotheses,
- developing marketing research plan according to the research goal,
- identifying the most appropriate (statistical) methods and tools,
- independent data analyses,
- cleaning the data and understanding them through the cleaning and descriptive statistics,
- testing hypotheses, especially using the bivariate and multivariate statistics,
- interpreting the obtained results, creating new knowledge,
- writing a research report and presenting it,
- acquiring, classifying, and analysing economical and non-economical business data and using them to support decision making,
- organising and coordinating the teamwork,
- differentiating of trustworthy and non-trustworthy information sources, using up to date knowledge obtained from professional literature,
- interconnecting information from economics, business management, and business informatics and using it for solving complex business problems,
presenting, defending, and reasoning professional opinion,
- communicating both in verbal and in writing with colleagues, clients, and business partners. - Syllabus
- Business research – a conceptual framework
- The basic forms of marketing research, research design
- Sampling, primary and secondary data
- Basic methods and tools of quantitative research
- Introduction to data mining (segmentation including RFM analysis)
- Data presentation and research report
- Application of methods and tools in a case study
- Literature
- required literature
- SAUNDERS, Mark, Philip LEWIS and Adrian THORNHILL. Research methods for business students. Eight edition. Harlow: Pearson, 2019, xxxiii, 83. ISBN 9781292208787. info
- recommended literature
- PUNCH, Keith. Úspěšný návrh výzkumu. Translated by Jan Hendl. Vydání druhé. Praha: Portál, 2015, 230 stran. ISBN 9788026209805. info
- MALHOTRA, Naresh K. Marketing research : an applied orientation. 6th ed., Global edition. Boston: Pearson, 2010, 929 s. ISBN 9780136094234. info
- FIELD, Andy. Discovering Statistics Using IBM SPSS Statistics. 5th. Sage Publishing, 2017. ISBN 978-1-5264-4578-0. URL info
- FIELD, Andy P., Jeremy MILES and Zoë FIELD. Discovering statistics using R. First published. Los Angeles: Sage, 2012, xxxiv, 957. ISBN 9781446200452. info
- OLSON, David L. Descriptive Data Mining. Online. 2017. ISBN 978-981-10-3340-7. Available from: https://dx.doi.org/10.1007/978-981-10-3340-7. URL info
- RABUŠIC, Ladislav, Petr SOUKUP and Petr MAREŠ. Statistická analýza sociálněvědních dat (prostřednictvím SPSS) (Statistical data analysis (with SPSS)). 2. přepracované vyd. Brno: Masarykova univerzita, 2019, 573 pp. ISBN 978-80-210-9247-1. URL info
- DISMAN, Miroslav. Jak se vyrábí sociologická znalost : příručka pro uživatele. 4. nezměněné vydání. Praha: Univerzita Karlova v Praze, nakladatelství Karolinum, 2011, 372 stran. ISBN 9788024619668. URL info
- Teaching methods
- The lectures will be devoted to the introduction of business research, its methods, tools and best practices. Such knowledge is applied at seminars.
- Assessment methods
- Active participation in the seminars and obtaining at least 60% of the test points is a condition for completing the course. The number of tests, their content, form, and dates are specified in the interactive syllabus available to all logged in to the Information System (i.e., even before enrolling in the course).
Any plagiarism in assignments during the semester, and copying, keeping a record of tests or carrying the tests out, using forbidden aids including any communication devices or any other breach of objectivity of the exam is regarded as a failure to meet the obligations of the course and as a serious breach of study regulations. As a consequence, the teacher grades the student with "F" or "N" and the dean is allowed to initiate a disciplinary action, which might lead to the termination of the studies.
Students studying abroad as part of the ERASMUS programme also have the conditions for completing the course specified in the interactive syllabus. - Language of instruction
- Czech
- Further Comments
- The course is taught annually.
The course is taught: every week.
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/econ/spring2025/MPH_EVPP