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Applied statistical modelling - Detailseite

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  • Online Belegung noch nicht möglich oder bereits abgeschlossen
Grunddaten
Veranstaltungsart Seminar/Hauptseminar Veranstaltungsnummer 3312133
Semester SoSe 2021 SWS 4
Rhythmus jedes 2. Semester Moodle-Link  
Veranstaltungsstatus Freigegeben für Vorlesungsverzeichnis  Freigegeben  Sprache englisch
Belegungsfrist - Eine Belegung ist online erforderlich Zentrale Frist    01.03.2021 - 07.04.2021   
Veranstaltungsformat Blended Course

Termine

Gruppe 1
Tag Zeit Rhythmus Dauer Raum Raum-
plan
Lehrperson Status Bemerkung fällt aus am Max. Teilnehmer
Do. 13:00 bis 17:00 wöch von 15.04.2021  Alfred Rühl-Haus - 0.223 Rudower Chaussee 16 (RUD16) - (Unterrichtsraum)   findet statt     20
Gruppe 1:
Zur Zeit keine Belegung möglich


Zugeordnete Person
Zugeordnete Person Zuständigkeit
Krüger, Tobias, Professor verantwortlich
Studiengänge
Abschluss Studiengang LP Semester
Master of Science  Global Change Geography Hauptfach ( Vertiefung: kein LA; POVersion: 2016 )   10  -  
Programmstud.-o.Abschl.MA  Global Change Geography Programm ( POVersion: 1999 )   10  -  
Zuordnung zu Einrichtungen
Einrichtungen
Mathematisch-Naturwissenschaftliche Fakultät, Geographisches Institut
Mathematisch-Naturwissenschaftliche Fakultät, Geographisches Institut, Abteilung Physische Geographie, Landschaftsökologie und Biogeographie
Inhalt
Kommentar

This is a course in Bayesian statistical modelling based on the textbook by McElreath (2020, 2nd ed.).

Learning objectives

Students ...

… have experienced and understood the fundamental philosophy behind Bayesian probability theory,

… have acquired the skills to do Bayesian analysis in STAN via interfaces from R,

… know which resources to consult for further study.

Topics

  • Fundamentals of Bayesian probability theory
  • Relationship with classical statistics
  • Linear models with one or more predictors
  • Generalised Linear Models
  • Multilevel models
  • Model predictive checking

Format

The mode of working is a mix of textbook study and collective discussion; exercises and collective problem solving; homework; and some lecture-style inputs from the teacher as needed. The students are required to take an active role in shaping the direction of the course.

The open source software STAN will be used from R via the 'brms' package. An introduction to and help with STAN and brms will be provided. A firm background in classical statistics and the software R is required, equivalent to a full grasp of “Quantitative Methods for Geographers”.

Allocation of places

Due to the mode of working in this course places are limited. Students are required to register via Agnes. Priority will be given to 4th semester students of the Global Change Geography Master. Remaining places will be allocated in the 1st class.

Literatur

McElreath 2020 (2nd ed.). Statistical Rethinking: A Bayesian Course with Examples in R and Stan. CRC Press

Gelman et al. 2020. Regression and Other Stories. Cambridge University Press

Prüfung

Students can choose from a set of projects at the end of the semester, which are like a extended homework. These need to be handed in using R Markdown just like the homework.

Zielgruppe

A firm background in classical statistics and the software R is required, equivalent to a full grasp of “Quantitative Methods for Geographers”.

Strukturbaum

Die Veranstaltung wurde 3 mal im Vorlesungsverzeichnis SoSe 2021 gefunden:

Humboldt-Universität zu Berlin | Unter den Linden 6 | D-10099 Berlin