040501 VO Foundations of Marketing: Data Analysis for Marketing Decisions (MA) (2023S)
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
Details
max. 60 Teilnehmer*innen
Sprache: Englisch
Prüfungstermine
N
Montag
22.05.2023
13:15 - 15:30
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Montag
26.06.2023
13:15 - 16:30
Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Montag
25.09.2023
13:15 - 16:30
Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Freitag
03.03.
09:45 - 11:15
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Montag
06.03.
09:45 - 11:15
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Freitag
10.03.
09:45 - 11:15
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Dienstag
14.03.
16:45 - 18:15
Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Montag
20.03.
09:45 - 11:15
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
N
Montag
27.03.
09:45 - 11:15
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Freitag
31.03.
13:15 - 14:45
Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Montag
17.04.
13:15 - 14:45
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Donnerstag
20.04.
13:15 - 14:45
Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Dienstag
02.05.
15:00 - 16:30
Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Montag
08.05.
13:15 - 14:45
Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Mittwoch
10.05.
13:15 - 14:45
Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
Students’ performance in the course is assessed through a comprehensive, final exam.
No material other than a dictonary may be used in the final exam.
No material other than a dictonary may be used in the final exam.
Mindestanforderungen und Beurteilungsmaßstab
In total, a minimum of 50 percent is needed to pass the course. The grading system is the following: 0 to 49% - grade 5, 50 to 59% - grade 4, 60 to 69% - grade 3, 70 to 79% - grade 2, 80 to 100% - grade 1.Students can take the exam for maximum 4 times. The additional registration for the exam is mandatory.
Prüfungsstoff
The final exam covers all topics discussed in the lectures and corresponding book chapters. The exam typically includes questions of different formats (e.g., true-false questions, single-choice questions, and mini cases with multiple-choice questions).
Literatur
Required 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].Recommended textbook: Field, A. (2018), Discovering Statistics Using IBM SPSS Statistics (5th edition), Sage Publications: London [ISBN: 9781526445780]. (previous editions are also fine)
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 20.03.2023 10:28
The course does not focus on programming/coding nor it aims to demonstrate how to use a specific statistical software (e.g, R, Excel, SPSS, JMP, Minitab, etc). Instead, it focuses on the logic, the implementation, and the interpretation of statistical data analysis in general – regardless of the program employed! Students who successfully complete DAMD will be equipped with a solid foundation of quantitative data analysis and be able to effectively understand, interpret, and communicate a wide range of analytical approaches; an essential asset for their professional development and career prospects.The sessions involve theory discussions accompanied by practical cases and hands-on examples. Data simulations and visualization tools are also employed to illustrate the theoretical/computational concepts discussed. Lectures typically provide background knowledge in understanding the theory and logic behind the statistical techniques and then illustrate how to interpret quantitative data analytic methods. Note that successful completion of DAMD depends greatly on whether students systematically review the relevant reading material.