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10538-01 - Lecture with practical courses: Statistics II: Reporting analysis (5 CP)

Semester spring semester 2026
Course frequency Every spring sem.
Lecturers Sarah Holzer (sarah.holzer@unibas.ch)
Sarah Musy (sarah.musy@unibas.ch, Assessor)
Michael Simon (m.simon@unibas.ch)
Diana Trutschel (diana.trutschel@unibas.ch)
Content • A lecture-seminar-exercise format will be used, with 30-60 minute lectures, 60 minute seminars and 60 minute exercises.
• Introduction to common statistical analysis such as exploratory data analysis, applied regression analysis, and common psychometric analyses explored with examples from health and nursing sciences.
• Development, execution and documentation of a statistical analysis.
• Implement robust processes for conducting and reporting the analysis.
• Practical training in R programming and analytical techniques.
Learning objectives Statistics is ubiquitous in medical and nursing research. Clinicians and nurse researchers need to understand basic statistical concepts, be able to interpret statistical results and conduct basic statistical analyses themselves. The course "Statistics II: Reporting analysis " is the second part of a course to learn statistics and to apply it in the statistical programming language R. The second part of this series focusses on planning and conducting analyses in health research.
The course will provide students the basis to understand and apply basic statistical techniques in the context of nursing research.
With the successful completion of the course students will be able to:
1. Understand basic concepts of statistics
2. Developing and applying a basic analytical plan
3. Implement statistical reporting for research papers
4. Apply principles of reproducible research
Bibliography Please bring your own laptop with an up-to-date installation of R and RStudio.
Instructions for installation: https://posit.co/download/rstudio-desktop/

It is expected that students know how to import data into R and do basic data manipulation. We recommend to revise the material from Statistics I: Basic concepts.

Helpful Sources
R reference card on ADAM
Cheat sheets on ADAM

Not mandatory books:
Fox, J., & Weisberg, S. (2010). An R companion to applied regression. Sage.
Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models: Cambridge University Press.

Literature in preparation of lectures will be posted online on ADAM.
Weblink Login ADAM

 

Admission requirements Nur für Studierende aus dem Studiengang Pflegewissenschaft.
Successful participation in “10537 - Statistics I".
Course application Anmelden: Belegen; Abmelden: Institut
Language of instruction English
Use of digital media Online, mandatory

 

Interval Weekday Time Room
wöchentlich Monday 09.15-12.00 Kollegienhaus, Hörsaal 117

Dates

Date Time Room
Monday 16.02.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 23.02.2026 09.15-12.00 Fasnachtsferien
Monday 02.03.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 09.03.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 16.03.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 23.03.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 30.03.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 06.04.2026 09.15-12.00 Ostern
Monday 13.04.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 20.04.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 27.04.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 04.05.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 11.05.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 18.05.2026 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 25.05.2026 09.15-12.00 Pfingstmontag
Modules Module Foundations of Quantitative and Qualitative Research (Master's Studies: Nursing)
Assessment format continuous assessment
Assessment details All students must participate in the group exercises in order to submit the report. Further information will be actively given per course start. The exam consist of a draft analysis (30 % for the course grade) and a written report (70 % of the course grade).

Please be aware it is not possible to repeat any of the exam's sections.
Assessment registration/deregistration Registration: course registration: deregistration: institute
Repeat examination no repeat examination
Scale 1-6 0,1
Repeated registration one repetition
Responsible faculty Faculty of Medicine
Offered by Institut für Pflegewissenschaft

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