| Dozent/in |
Dr. rer. soc. Brigitte Hofstetter Furrer; Lukas Kauer, PhD |
| Veranstaltungsart |
Vorlesung |
| Code |
HS251082 |
| Semester |
Herbstsemester 2025 |
| Durchführender Fachbereich |
Gesundheitswissenschaften |
| Studienstufe |
Master |
| Termin/e |
Fr, 19.09.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 26.09.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 03.10.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 10.10.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 17.10.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 24.10.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 31.10.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 07.11.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 14.11.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 21.11.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 28.11.2025, 08:15 - 12:00 Uhr, ZOOM
Fr, 05.12.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 12.12.2025, 08:15 - 12:00 Uhr, HS 8
Fr, 19.12.2025, 08:15 - 12:00 Uhr, HS 8 |
| Umfang |
4 Semesterwochenstunden |
| Inhalt |
The course part Quantitative Methods covers the following topics:
• Basic concepts: Measuring, estimating, testing, and forecasting
• Basics of descriptive statistics: Scale levels, statistical parameters
• Basics of inferential statistics: Sample and population, probabilities, random variables, and distribution families, basic elements of hypothesis testing
• Investigation of differences: Procedures for one- and two-group comparisons
• Analysis of dependencies: Regression and Ordinary Least Squares
The course part Qualitative Methods covers the following topics:
• Setting the scene: theoretical frameworks, ontological positions, main features and uses of qualitative research
• Designing qualitative research: initial steps, research approaches, ethical issues
• Generating data: sampling strategies, narrative and semi-structured interviews, focus groups, observation
• Analysis of qualitative data: analytic strategies, processing, and coding data
• Interpreting and reporting data: description, explanation, generalization in qualitative research, displaying qualitative evidence
• Quality criteria in qualitative research |
| E-Learning |
Course materials are provided or linked, and exercises handed in via the e-learning platform Moodle. |
| Lernziele |
The overarching goal of the course Basic Research Methods is for incoming students to obtain a foundation in qualitative and quantitative research methods for the start of their studies in the M. Sc. in health sciences.
The main goal in the Quantitative Methods part is to understand why quantitative methods are important in health sciences and how they work. Instructions focus on statistical foundations and the basic statistical methods most commonly used in the health sciences. Students will learn how to apply them with the statistical software R. After taking this course, students
- Can describe and differentiate the main approaches to quantitative data analysis
-Understand basic statistical concepts such as central tendency, spread, and association
- Understand principles of statistical inference
- Can produce simple univariate and bivariate statistics
- Can interpret results from statistical analyses of bivariate relationships and group differences
In the Qualitative Methods part, students will familiarize themselves with the methodological foundations and theoretical assumptions of qualitative research. They will learn about qualitative research designs in health sciences and understand the underlying research process. Furthermore, students will be able to assess the advantages and disadvantages of common data collection and analysis methods and get to know the challenges associated with qualitative research methods. |
| Voraussetzungen |
Prerequisites:
Basic knowledge of the software R is required. Details on how to familiarize yourself with the software will be provided by email at the end of August. Please bring your own laptop with a recent version of RStudio installed. RStudio is freely available on: https://posit.co/download/rstudio-desktop/
Basic knowledge of qualitative methods and of statistics is an advantage, but not a requirement.
Requirements for successful completion of the course:
Overall grade of 4.0 or better. The grade will be the mean of the quantitative and qualitative parts. If you do not successfully complete the course (mean < 4.0), you must repeat the entire written exam (quantitative and qualitative part). If you must retake the exam, the partial grade (20% of group work, part Quantitative Methods) you achieved during the course will be transferred for the calculation of the final grade of the repeat exam (no retake of group work possible). |
| Sprache |
Englisch |
| Anmeldung |
https://elearning.hsm-unilu.ch/course/view.php?id=919
|
| Prüfung |
Part Quantitative Methods: Submission and presentation of the solutions to an exercise sheet during the semester by small groups of students (20% of the grade for the course part Quantitative Methods) and written exam during the exam session at the end of the semester (80% of the grade for the course part Quantitative Methods).
Part Qualitative Methods: Written exam during the exam session at the end of the semester (100% of the grade for the course part Qualitative Methods).
IMPORTANT: In order to earn credits and participate at the exam registration via Uni Portal within the exam registration period is MANDATORY. Further information: www.unilu.ch/en/study/courses-exams-regulations/health-sciences-and-medicine/exams/ |
| Abschlussform / Credits |
Written exmination / 6 Credits
|
| Hinweise |
Teaching methods:
Part Quantitative Methods: Every lecture is followed by an exercise session in the following week. In the lectures, the focus is on the theoretical background. In the exercises, small groups of students present their solutions in R to the exercises on topics from the previous lecture.
Part Qualitative Methods: The mandatory reading and input presentations provide the theoretical foundation for the written exam. Discussions and small in-class exercises help consolidate the theoretical input and prepare students for its future application in practical contexts. |
| Hörer-/innen |
Ja |
| Kontakt |
brigitte.hofstetter@unilu.ch / lukas.kauer@unilu.ch |
| Material |
Lecture slides, mandatory readings, exercise materials and other documents for the course are provided or linked on Moodle.
Part Quantitative Methods: For the exercises during the course, the students work on their own laptops, on which they have installed the statistical software RStudio and topic-specific R packages. R and RStudio are freely available on: https://posit.co/download/rstudio-desktop/. Details on how to familiarize yourself with the software will be provided by email in advance. |
| Literatur |
Further readings/textbooks on quantitative research:
• Perry, L. Introduction to Statistics, bookdown.org
• Diez, D., Çetinkaya-Rundel, M., Barr, C.D. (2019). OpenIntro Statistics, https://leanpub.com/os
• Phillips, N. D. (2018). YaRrr! The Pirate’s Guide to R, bookdown.org
• Field., A., Miles, J., Field, Z. (2012). Discovering Statistics Using R. Sage.
Further readings/textbooks on qualitative research:
• Bourgeault, I., Dingwall, R. & De Vries, Raymond (2010) Handbook of Qualitative Methods in Health Research. Sage.
• Bryman, A., Bell, E. A., Reck, J. & Fields, J. (2022). Social Research Methods. Oxford University Press.
• Creswell, J. W. & Poth, C. N. (2018). Qualitative Inquiry and Research Design. Choosing Among Five Approaches (4th ed.). Sage.
• Patton, M. Q. (2015). Qualitative Research & Evaluation Methods. Theory and Practice (4th ed.). Sage.
• Pope, C. & Mays, N. (Eds.) (2020). Qualitative Research in Health Care (4th ed.). Wiley Blackwell. |