Universität Wien FIND

040213 UK Repetitorium: Data Analysis for Marketing Decisions in practice (2023S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Prüfungsimmanente Lehrveranstaltung


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


max. 30 Teilnehmer*innen
Sprache: Englisch


Termine (iCal) - nächster Termin ist mit N markiert

Freitag 05.05. 09:45 - 13:00 PC-Seminarraum 2 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Freitag 12.05. 13:15 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Montag 22.05. 09:45 - 13:00 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Freitag 26.05. 13:15 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Freitag 02.06. 09:45 - 13:00 PC-Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Untergeschoß


Ziele, Inhalte und Methode der Lehrveranstaltung

Quantitative methods, data analytics, and statistical analysis is a key component of decision-making
for business practitioners and policy makers. This course aims to equip students with the hands-on
knowledge and skills necessary to implement, interpret, and communicate quantitative data analysis
using computer software and other tools.

The course assumes that students already have a theoretical understanding of statistical inference and
basic knowledge of key concepts in research methods. Hence, the emphasis is not placed on analytical
theory, but on training students in analyzing data to predict behavioral tendencies (e.g., relative product
preferences, purchase choices, and willingness to pay), make forecasts about future outcomes (e.g.,
likelihood of customer switching, probability of being hired/fired, and expected product sales), make
comparisons (e.g., across gender, nationality, or market segments), and assess the efficacy of alternative

The course primarily relies on the IBM SPSS software, but also utilizes additional statistical packages
and tools such as PROCESS, JAMOVI and G*Power. Overall, the course provides students with a toolbox
of practical skills that are essential in carrying out empirical projects.

The sessions involve a brief introduction to the underlying logic behind the different analytical methods
and then focus on hands-on demonstrations and exercises. Sessions are highly interactive with
students working individually and/or in groups to solve practical problems in class using specific tools
and software under the guidance of the professor who will also provide feedback on how to effectively
perform, report, and interpret the various analytical techniques.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Students’ performance in the course is assessed on the following dimensions:
▪ Participation
▪ Group exercises
▪ Final group assignment

Mindestanforderungen und Beurteilungsmaßstab

The Repetitorium DAMDiP does not result in a numerical grade. Students receive either a “+” (pass) or
a “─“ (fail), depending on whether they have performed adequately in the assessment dimensions
mentioned above.


Students mainly work in groups to address business research questions that require performing quantitative
data analysis and presenting the results. The exercises focus on individual statistical techniques
and typically take place during the sessions. The final group assignment consists of a more comprehensive
case study, where groups are requested to identify, perform, and report the appropriate analyses
to address several different questions. Class interaction and students’ participation is highly recommended
to ensure effective learning.


Required textbook: Field, A. (2018), Discovering Statistics Using IBM SPSS Statistics (5th edition), Sage
Publications: London [ISBN: 9781526445780].

Recommended additional textbook: Diamantopoulos, D., Schlegelmilch, B., & Halkias, G. (2023), Taking
the Fear out of Data Analysis: Completely Revised, Significantly Extended and Still Fun, Edward Elgar:
London [ISBN: 978 1 80392 985 9].

Complementary material: Marshall, E. (2016), The Statistics Tutor’s Quick Guide to Commonly Used
Statistical Tests, University of Shefield - Statstutor Community Project, [Retrieved from www.statstutor.
ac.uk]. → this and other open-access material will be available on Moodle

Zuordnung im Vorlesungsverzeichnis

Letzte Änderung: Mo 20.03.2023 10:28