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67551-01 - Seminar: Empirical Studies of Art and Literature Reception: Statistics using R 3 KP

Semester Frühjahrsemester 2023
Angebotsmuster unregelmässig
Dozierende Moniek Kuijpers (moniek.kuijpers@unibas.ch, BeurteilerIn)
Inhalt In the past decades interest has grown in scientific approaches to aesthetic artefacts, may they be literary texts, visual artworks, films or even performances. This interest stems from a desire to investigate these aesthetic objects in a more rigorous, scientific way. The results of such investigations help us cultivate a deeper understanding of aesthetic phenomena and, perhaps more importantly, what they mean to individuals and societies.

With scientific approaches to the study of art – and of literature in particular – come statistical analyses of data gathered using said scientific approaches. This course will teach students to use statistics to answer empirical research questions in various areas of scientific studies of literature and art reception. The students will receive instructions on how to utilize the open-source software program R to run statistical code.

This course is open for MA students from the (digital) humanities. Be advised that the course will be in English and that you will be asked to discuss, present and write in English.

The course comprises 6 blocks

The seminars take place on these days:
- Friday 24.02.2023 10:00-12:30 and 14:00-16:30
- Friday 10.03.2023 10:00-12:30 and 14:00-16:30 online
- Friday 24.03.2023 10:00-12:30 and 14:00-16:30
- Friday 21.04.2023 10:00-12:30 and 14:00-16:30
- Friday 28.04.2023 10:00-12:30 and 14:00-16:30
- Friday 26.05.2023 15:00-17:00 (final poster session)

In between seminars you will work on developing your own empirical research project in groups, read up on empirical papers assigned to the reading list, and run statistical analyses for your own project. You can make an appointment to come in during office hours (Tuesday between 13:00 and 15:00 or Thursday between 10:00 and 12:00) to discuss your research project.
Lernziele The overarching learning objective is to learn basic statistical skills using R.
To achieve this aim, students will read up on scientific papers covering a range of relevant topics in the field of empirical literary studies, they will discuss these papers in class, take part in hands-on sessions to practice running statistical tests using R, and writing a research report (in the form of a poster) in which they demonstrate their knowledge of data visualization and empirical hypothesis testing using statistics in R.
Literatur The reading list for this course will be made available 2 to 3 weeks before class.


Teilnahmebedingungen The number of participants is limited. In case of over-subscription, students of Digital Humanities will be admitted preferentially.
Unterrichtssprache Englisch
Einsatz digitaler Medien kein spezifischer Einsatz


Intervall Wochentag Zeit Raum
Block Siehe Einzeltermine


Datum Zeit Raum
Freitag 24.02.2023 10.00-16.30 Uhr Bernoullistrasse 14/16, Kleiner Seminarraum 02.001
Freitag 10.03.2023 10.00-16.30 Uhr Bernoullistrasse 14/16, Kleiner Seminarraum 02.001
Freitag 24.03.2023 10.00-16.30 Uhr Bernoullistrasse 14/16, Kleiner Seminarraum 02.001
Freitag 21.04.2023 10.00-16.30 Uhr Bernoullistrasse 14/16, Kleiner Seminarraum 02.001
Freitag 28.04.2023 10.00-16.30 Uhr Bernoullistrasse 14/16, Kleiner Seminarraum 02.001
Freitag 26.05.2023 15.00-17.00 Uhr Bernoullistrasse 14/16, Kleiner Seminarraum 02.001
Module Modul: Creating, Analyzing and Visualizing of Data (Master Studienfach: Digital Humanities)
Modul: Forschungspraxis und Vertiefung (Master Studiengang: Sprache und Kommunikation)
Modul: Sprache als Prozess (Master Studiengang: Sprache und Kommunikation)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung Students will analyze experimental data they have collected themselves to answer an empirical research question they developed themselves using the right statistical testing. They will report on this study in the form of a poster presentation.
This report will be assessed as either a pass or a fail.
An-/Abmeldung zur Leistungsüberprüfung Anmelden: Belegen; Abmelden: nicht erforderlich
Wiederholungsprüfung keine Wiederholungsprüfung
Skala Pass / Fail
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Philosophisch-Historische Fakultät, studadmin-philhist@unibas.ch
Anbietende Organisationseinheit Digital Humanities Lab