040501 VO Foundations of Marketing: Data Analysis for Marketing Decisions (MA) (2022W)
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GEMISCHT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
Details
Sprache: Englisch
Prüfungstermine
- Freitag 16.12.2022 10:45 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
- Montag 23.01.2023 13:15 - 16:30 Seminarraum 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Montag 20.02.2023 11:30 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
- Montag 03.10. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Freitag 07.10. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Freitag 14.10. 09:45 - 11:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Freitag 21.10. 09:45 - 11:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Freitag 28.10. 09:45 - 11:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Montag 07.11. 09:45 - 11:15 Digital
- Freitag 11.11. 11:30 - 13:00 Digital
- Freitag 18.11. 11:30 - 13:00 Digital
- Freitag 25.11. 11:30 - 13:00 Digital
- Montag 05.12. 13:15 - 14:45 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
- Freitag 09.12. 09:45 - 11:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
- Montag 12.12. 11:30 - 13:00 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Sound knowledge of statistics and data analysis is an essential requirement for marketing research and managerial decision-making – more than one would expect! The present course discusses (a) key concepts of statistics and statistical inference (e.g., NHST, Type I and II error, confidence intervals) and (b) different methods of data analysis (e.g., t-test, χ2 test, ANOVA, regression analysis) in a series of lectures that combine theory, illustrative examples, and hands-on exercises. The course is not tied to a any specific statistical software (IBM SPSS software is only used for demonstration). Rather it focuses on the logic, the implementation, and the interpretation of statistical data analysis in general – regardless of the program used. Students who successfully complete DAMD will be equipped with the ability to effectively carry out data analysis projects in their later academic and professional career.The sessions involve theory discussions accompanied by practical examples and hands-on exercises. Lectures primarily 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 class material.
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.
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: Field, A. (2013), Discovering Statistics Using SPSS (4th edition), Sage Publications: London [ISBN: 9781446249185] OR (new edition): Field, A. (2018), Discovering Statistics Using IBM SPSS Statistics (5th edition), Sage Publications: London [ISBN: 9781526445780].Recommended additional textbook: Diamantopoulos, D. and Schlegelmilch, B. (2000), Taking the Fear out of Data Analysis (2nd edition), South-Western CENGAGE Learning: London [ISBN: 978-1-86152-430-0].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]. → will be available on Moodle
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Do 11.05.2023 11:27