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| Semester | Frühjahrsemester 2024 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende |
Catherine Blatter (catherine.blatter@unibas.ch)
Sarah Musy (sarah.musy@unibas.ch) Michael Simon (m.simon@unibas.ch, BeurteilerIn) Diana Trutschel (diana.trutschel@unibas.ch) |
| Inhalt | • 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. |
| Lernziele | 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 |
| Literatur | 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 |
| Teilnahmebedingungen | Nur für Studierende aus dem Studiengang Pflegewissenschaft. Successful participation in “10537 - Statistics I". |
| Anmeldung zur Lehrveranstaltung | Anmelden: Belegen; Abmelden: Institut |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | Online-Angebot obligatorisch |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Montag | 09.15-12.00 | Kollegienhaus, Hörsaal 117 |
| Datum | Zeit | Raum |
|---|---|---|
| Montag 26.02.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 04.03.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 11.03.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 18.03.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 25.03.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 01.04.2024 | 09.15-12.00 Uhr | Ostern |
| Montag 08.04.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 15.04.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 22.04.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 29.04.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 06.05.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 13.05.2024 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 117 |
| Montag 20.05.2024 | 09.15-12.00 Uhr | Pfingstmontag |
| Montag 27.05.2024 | 09.15-17.30 Uhr | Bernoullistrasse 28, Seminarraum U01 |
| Montag 03.06.2024 | 09.15-17.30 Uhr | Bernoullistrasse 28, Seminarraum 7 |
| Module |
Modul Grundkenntnisse der quantitativen und qualitativen Forschung (Masterstudium: Pflegewissenschaft) |
| Leistungsüberprüfung | Lehrveranst.-begleitend |
| Hinweise zur Leistungsüberprüfung | The exams consist of a data preparation (20% of the course grade), a descriptive analysis (20% of the course grade), an inferential analysis (20% of the course grade), and an oral exam (40% of the course grade). Please be aware it is not possible to repeat any of the exam's sections. Die mündlichen Prüfungen finden an zwei Tagen statt, Details folgen. |
| An-/Abmeldung zur Leistungsüberprüfung | Anmelden: Belegen; Abmelden: Institut |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,1 |
| Wiederholtes Belegen | einmal wiederholbar |
| Zuständige Fakultät | Medizinische Fakultät |
| Anbietende Organisationseinheit | Institut für Pflegewissenschaft |