Universität Wien

220076 VO VO Introduction to Data Analysis (2018W)

3.00 ECTS (2.00 SWS), SPL 22 - Publizistik- und Kommunikationswissenschaft
Moodle

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Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Prüfungstermine

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

"VO Introduction to Data Analysis" is complementary to "UE Applied Data Analysis". The course will start wit the VO on Oct 16. From then onwards, we will meet every week (UE/VO altering), except for the winter break. The last meeting, in which we will also write the exam, takes place on Jan 29.

  • Dienstag 16.10. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Dienstag 30.10. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Dienstag 13.11. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Dienstag 27.11. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Dienstag 11.12. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Dienstag 15.01. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II
  • Freitag 25.01. 09:45 - 11:15 Seminarraum 1 2H316 UZA II Rotunde
  • Dienstag 29.01. 13:15 - 14:45 EDV-Raum 4 2C502 5.OG UZA II

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The objective of this class is to make students acquaintance with basic theoretical and practical statistical and quantitative research concepts in communication research. After the completion of the class, students should be able to plan and construct most commonly needed quantitative analyses in our field based on their own quantitative research designs.

The content of the class will generically cover fundamental mathematical processes for all statistical tests. However, more emphasis will be placed on the general understanding of all necessary methodological concepts to execute quantitative empirical tests with R.

Students will be proficient interpreting R outputs, creating tables ready to be published in academic journals, and discussing as well as interpreting most common quantitative findings in our field.
In sum, the overall goal of the class is to provide students with the necessary conceptual and practical skills to feel comfortable collecting and analyzing data based on their own research questions and designs.

In order to do so, the following topics will be covered:

Introduction to Statistical Methods (e.g., mean, variance, standard deviation)
Introduction to R / R workspace
R Data Handling (enter, edit and save data)
Exploring Assumptions for Analyses
Exploring Data with Graphs in R (scatterplot, histograms, boxplots)
Correlation
Regression
Exploratory Factor Analysis
Comparing Two Means (T-Test)
ANOVA / ANCOVA
Elective topics: Logistic Regression, MANOVA, Latex etc.

Attention: The courses VO Introduction to Data Analysis and UE Applied Data Analysis are linked. Phases of lecture and exercise will alternate.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Assessment will be based on the following course requirement:
Final Exam (Open Questions, R Analysis Tasks and Discussion): 100%

Mindestanforderungen und Beurteilungsmaßstab

Prüfungsstoff

Literatur

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Sa 02.04.2022 00:23