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68792-01 - Seminar: Bayesian Multilevel Models using R 1 KP

Semester Frühjahrsemester 2023
Angebotsmuster unregelmässig
Dozierende Angela Leipold (angela.leipold@unibas.ch, BeurteilerIn)
Inhalt Dieser Worksop wird von Prof. Dr. Emma Zang (Yale University) angeboten.

This workshop will introduce you to modern Bayesian methods for
analysis and inference in R, with a special focus on Bayesian
hierarchical models. Bayesian inference and estimation offer a number
of benefits, including the fact that it allows the kinds of inferences
that scientists have always wanted to make about hypotheses, models,
and parameters. For example, relying on the results of Bayesian
analysis, researchers can make direct claims about the support for a
model or a hypothesis, such as: "the probability that an effect of X
on Y is greater than zero is .99;" or "Model A is twice probable as
Model B". The reason why these types of intuitive inferences can be
made is that Bayesian methods calculate the probability of parameters,
models, or hypotheses directly. This stands in stark contrast to more
traditional types of statistical analysis, which can only calculate
the probability of an observed dataset -- this is partly why
traditional concepts such as standard errors, p-values, and confidence
intervals are less intuitive than their Bayesian counterparts.

This workshop will introduce you to the Bayesian way of thinking about
scientific inference and estimation, focusing on the application of Bayesian
hierarchical models through multiple worked examples in R. By the conclusion of the
workshop, you will have a working knowledge of the Bayesian approach
to inference, and an understanding of what distinguishes it from the
traditional (frequentist) approach. You will
also understand how to use Bayesian workflows to develop and validate
models. Finally, you will learn how to apply Bayesian hierarchical models appropriately for your research questions, especially when you have small sample sizes.
Bemerkungen Dies ist ein Angebot des Doktoratsprogramms SED-PSY.

Maximale Anzahl Studierende: 15.

Auswahlkriterien bei Überbelegung:
1) Doktorierende SED-PSY
2) Masterstudierende SWE Science Track
3) Doktorierende anderer Vertiefungsrichtungen

SED-PSY rules for withdrawal, absence, or partial course attendance:

If you cannot attend a workshop that you have signed up for, please cancel your course registration as soon as possible by sending an e-mail to angela.leipold@unibas.ch. This will allow other PhD students interested in the course to move up from the waiting list. The SED-PSY strongly values fairness. After the university’s official registration period has ended, cancelled course will be assessed with NE. Course registrations can be cancelled until one week before the workshops begins. In the case of late cancellations, participants will not be considered for course registration in the next three months of the lecture periods and will be removed from the registration list of any course they have signed up during these three upcoming months of the lecture periods.

If an urgent, unforeseeable, or inevitable event before or during the workshop prevents a participant from attending, a written and substantiated withdrawal request that includes appropriate documentation (e.g. a doctor’s note) must be submitted to angela.leipold@unibas.ch within two days of the workshop and without being prompted. The program director decides on the approval of the withdrawal request.

ECTS-points are awarded only for 100% course attendance.


Teilnahmebedingungen Doktorat im Bereich SED-PSY.

Für Masterstudierende im SWE Science Track: Anmeldung und erfolgreiche Aufnahme in den SWE Science Track.
Siehe: https://www.psychologie.unibas.ch/de/studium/doktoratsstudium/doktoratsprogramme/sozial-wirtschafts-und-entscheidungspsychologie/master-science-track/
Unterrichtssprache Englisch
Einsatz digitaler Medien Online-Veranstaltung


Intervall Wochentag Zeit Raum
unregelmässig Siehe Einzeltermine
Bemerkungen 8.-9.3.23: Mittwoch 15.00 - 19.00, Donnerstag 15.00-19.00


Datum Zeit Raum
Mittwoch 08.03.2023 15.00-19.00 Uhr - Online Präsenz -, --
Donnerstag 09.03.2023 15.00-19.00 Uhr - Online Präsenz -, --
Module Doktorat Psychologie: Empfehlungen (Promotionsfach: Psychologie)
Modul: Science Track Sozial-, Wirtschafts- und Entscheidungspsychologie (Masterstudium: Psychologie)
Leistungsüberprüfung Lehrveranst.-begleitend
An-/Abmeldung zur Leistungsüberprüfung Anm.: Belegen Lehrveranstaltung; Abm.: stornieren
Wiederholungsprüfung keine Wiederholungsprüfung
Skala Pass / Fail
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Fakultät für Psychologie, studiendekanat-psychologie@unibas.ch
Anbietende Organisationseinheit Fakultät für Psychologie