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| Semester | Frühjahrsemester 2022 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende |
Catherine Blatter (catherine.blatter@unibas.ch)
Sarah Naima Musy (sarah.musy@unibas.ch) Michael Simon (m.simon@unibas.ch, BeurteilerIn) |
| 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 an analyses plan • Introduction to and application of principles of reproducible research. • 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 "Understanding statistics with R (2)" 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://www.rstudio.com/products/rstudio/download/ If you would like to brush up your R skills, please consider to participate in one of the numerous online tutorials. To get everything set-up: 1) Datacamp: https://www.datacamp.com/courses/free-introduction-to-r 2) EdX: https://www.edx.org/course/explore-statistics-r-kix-kiexplorx-0 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. |
| Bemerkungen | Einsatz digitaler Medien. Unterrichtssprache: Deutsch & Englisch |
| 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 114 |
| Datum | Zeit | Raum |
|---|---|---|
| Montag 21.02.2022 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 114 |
| Montag 28.02.2022 | 09.15-12.00 Uhr | - Online Präsenz -, -- |
| Montag 07.03.2022 | 09.15-12.00 Uhr | Fasnachtsferien |
| Montag 14.03.2022 | 09.15-12.00 Uhr | - Online Präsenz -, -- |
| Montag 21.03.2022 | 09.15-12.00 Uhr | - Online Präsenz -, -- |
| Montag 28.03.2022 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 114 |
| Montag 04.04.2022 | 09.15-12.00 Uhr | - Online Präsenz -, -- |
| Montag 11.04.2022 | 09.15-12.00 Uhr | - Online Präsenz -, -- |
| Montag 18.04.2022 | 09.15-12.00 Uhr | Ostern |
| Montag 25.04.2022 | 09.15-12.00 Uhr | - Online Präsenz -, -- |
| Montag 02.05.2022 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 114 |
| Montag 09.05.2022 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 114 |
| Montag 16.05.2022 | 09.15-12.00 Uhr | - Online Präsenz -, -- |
| Montag 30.05.2022 | 09.15-12.00 Uhr | Kollegienhaus, Hörsaal 114 |
| Module |
Modul Grundkenntnisse der quantitativen und qualitativen Forschung (Masterstudium: Pflegewissenschaft) |
| Leistungsüberprüfung | Lehrveranst.-begleitend |
| Hinweise zur Leistungsüberprüfung | The exams consist of a written analysis plan (pass/fail, 10% of the course grade), 10% abstract and 80% written report. Please be aware it is not possible to revise the written report. |
| 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 |