Universität Wien FIND
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122252 AR Linguistics Course (Advanced 1-5) - Hist. & Descr. (2017S)

Introduction to statistical modeling for linguists

5.00 ECTS (2.00 SWS), SPL 12 - Anglistik
Prüfungsimmanente Lehrveranstaltung

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Donnerstag 16.03. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Samstag 18.03. 10:00 - 14:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 27.04. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Samstag 29.04. 10:00 - 14:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 18.05. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Samstag 20.05. 10:00 - 14:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Donnerstag 22.06. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Samstag 24.06. 10:00 - 14:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This course provides an introduction to multivariate statistical modeling (more specifically, regression models) with a particular focus on the analysis of data coming from various subareas of linguistic research, such as general linguistics, sociolinguistics, PPN linguistics, historical linguistics, or first/second language acquisition research.

The first part of the course introduces descriptive as well as inferential statistics, i.e. measures of central tendency and variability, parameter estimation and confidence intervals (as well as a quick introduction to hypothesis testing). In the second part of the course, we will consider various regression-model families (linear models, logistic regression, generalized linear models, mixed effects models) which can be used to analyze the impact of multiple predictor (independent) variables on a single outcome (dependent) variable.

The course is partially based on Butler (1985), "Statistics in linguistics". Since this is a Blocklehrveranstaltung, students are advised to read the first couple of chapters for the first session and hand in a pre-course exercise (for details see moodle). More literature to be provided in class.

For calculating purposes, the statistical software package R together with the frontend RStudio will be used. Both are already installed on the PCs in the PC labs. Since most of the assignments will require calculations with R(Studio), the correct version of this software is needed to be installed on your own computer.

No previous knowledge of statistics or statistical software is required but a solid knowledge of high school mathematics (at least Unterstufe) will prove useful (linear functions, basic arithemtical operations, fractions, percentages etc.).

Art der Leistungskontrolle und erlaubte Hilfsmittel

Pre-course exercise, four home assignments, and participation in class

Mindestanforderungen und Beurteilungsmaßstab

The ability to analyze, present and describe quantitative linguistic data as well as the ability to understand and interpret statistical analyses and relevant statistical parameters.

Assessment:
Pre-course exercise: 5%
Four home assignments: 20% each
Participation in class: 15%
Minimum pass grade: 60% in total

Prüfungsstoff

Literatur


Zuordnung im Vorlesungsverzeichnis

Studium: UF 344; MA 812 [2]; MA 812 [2]; UF MA 046
Code/Modul: UF 4.2.3-223-225, MA M05, MA M04, M05, UF MA 4B
Lehrinhalt: 12-0330

Letzte Änderung: Mo 07.09.2020 15:33