Universität Wien

220076 VO VO Introduction to Data Analysis (2023W)

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

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Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
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Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

First session on Oct 10 will be online only. Check your e-mail and the information on Moodle!
First in-class session will be on Oct 17.

Please note: This is a joint course in the module 2 of the restricted-access MSc “Communication Science”. You may only earn credits for this course if you have been selected and admitted in the application process for this program.

  • Tuesday 10.10. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 17.10. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 24.10. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 31.10. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 07.11. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 14.11. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 21.11. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 28.11. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 05.12. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 12.12. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 09.01. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 16.01. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 23.01. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG
  • Tuesday 30.01. 13:15 - 14:45 Seminarraum 9, Währinger Straße 29 2.OG

Information

Aims, contents and method of the course

The main goal of the course is to introduce students to the quantitative methods for conducting meaningful inquiry in communication research and provide them with practical knowledge of available statistical software tools. The course will cover all steps of data analysis from preparing and cleaning data to the choice of analytical approaches, and interpretation of the results, using current software tools. Students will gain an overview of research intent and design, methodology and technique, format and presentation, and data management and analysis informed by commonly used statistical methods. At the end of this class, students will acquire necessary conceptual and practical knowledge to collect and analyze data based on own research questions and designs.

Attention: The courses VO Introduction to Data Analysis and UE Applied Data Analysis are linked

Assessment and permitted materials

Written exam

Minimum requirements and assessment criteria

Grading:
A = 1 (Very Good): 87 - 100%
B = 2 (Good): 75 - 86,99%
C = 3 (Satisfying): 63 - 74,99%
D = 4 (Sufficient): 50 - 62,99%
F = 5 (Not Sufficient): 00 - 49,99%
Class attendance is mandatory. You need to actively participate in at least 80% of the sessions.

Examination topics

All contents discussed in the course and documented on Moodle.

Reading list

Llaudet, E. & Imai, K. (2023). Data Analysis for Social Science: A Friendly and Practical Introduction. Princeton University Press.

Ismay, C. & Kim, A. Y. (2020). Statistical Inference via Data Science: A Modern Dive into R and the Tidyverse. CRC Press.

More relevant literature will be announced in the syllabus.

Association in the course directory

Last modified: Mo 09.10.2023 09:28