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

Semester spring semester 2023
Course frequency Every spring sem.
Lecturers Catherine Blatter (catherine.blatter@unibas.ch)
Sarah Musy (sarah.musy@unibas.ch)
Michael Simon (m.simon@unibas.ch, Assessor)
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 an analyses plan
• Introduction to and application of principles of reproducible research.
• 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 installed R and RStudio.
1) Install R: https://cran.r-project.org/
2) Install RStudio: 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 20.02.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 27.02.2023 09.15-12.00 Fasnachstferien
Monday 06.03.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 13.03.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 20.03.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 27.03.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 03.04.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 10.04.2023 09.15-12.00 Ostern
Monday 17.04.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 24.04.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 01.05.2023 09.15-12.00 Tag der Arbeit
Monday 08.05.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 15.05.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Monday 22.05.2023 09.15-12.00 Kollegienhaus, Hörsaal 117
Modules Modul Grundkenntnisse der quantitativen und qualitativen Forschung (Master's Studies: Nursing)
Assessment format continuous assessment
Assessment details The exams consist of a written analysis plan (10% of the course grade), an abstract (10% of the course grade), and a written report (80% of the course grade).

Please be aware it is not possible to revise the written report.
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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