220077 UE UE Applied Data Analysis (2022W)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 19.09.2022 09:00 bis Mi 21.09.2022 18:00
- Abmeldung bis Mo 31.10.2022 23:59
Details
max. 30 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Mittwoch 12.10. 13:15 - 16:15 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Mittwoch 19.10. 13:15 - 16:15 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Mittwoch 09.11. 13:15 - 16:15 Seminarraum 7, Währinger Straße 29 1.OG
- Mittwoch 23.11. 13:15 - 16:15 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Mittwoch 07.12. 13:15 - 16:15 Lehrredaktion Publizistik, Währinger Straße 29 2.OG
- Mittwoch 18.01. 13:15 - 16:15 Seminarraum 3, Währinger Straße 29 1.UG
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
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 analyse data based on own research questions and designs.Attention: The courses VO Introduction to Data Analysis and UE Applied Data Analysis are linked
Art der Leistungskontrolle und erlaubte Hilfsmittel
Grading:
- 60% homework assignments
- 40% in-class exercisesTwo homework assignments:
Homework 1: 25%
Homework 2: 35%To receive a positive grade for the course, students must submit both homework assignments before the deadline and achieve an average of 50% of the total homework assignment points.Online attendance will be evaluated via different Moodle tools.
- 60% homework assignments
- 40% in-class exercisesTwo homework assignments:
Homework 1: 25%
Homework 2: 35%To receive a positive grade for the course, students must submit both homework assignments before the deadline and achieve an average of 50% of the total homework assignment points.Online attendance will be evaluated via different Moodle tools.
Mindestanforderungen und Beurteilungsmaßstab
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 are allowed to miss only one session (3 hours). Attendance of the first session (on site) is mandatory for all.
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 are allowed to miss only one session (3 hours). Attendance of the first session (on site) is mandatory for all.
Prüfungsstoff
The homework assignments will cover the material discussed in the sessions.
Literatur
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Do 20.10.2022 09:50