Universität Wien
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040268 KU Building Blocks of Marketing 2: Quantitative Methods (MA) (2024W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle
Tu 21.01. 11:30-13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Registration/Deregistration

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

Details

max. 24 participants
Language: German, English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 08.10. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 15.10. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 22.10. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 29.10. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 05.11. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 12.11. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 19.11. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 26.11. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 03.12. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 10.12. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 17.12. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 07.01. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 14.01. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 28.01. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Aims, contents and method of the course

Participants will get to know the most common quantitative methods and analytical techniques that are used in management and marketing research. They will learn how to analyze data and perform statistical analysis with SPSS. They will further learn how to evaluate and interpret quantitative analysis procedures and results that are performed by scholars and by research institutions (e.g., market research companies).

The primary objective of the course will be achieved through on-site meetings. Students will follow the lecture and complete several computer assignments under the supervision of the instructor. Lectures typically provide background knowledge in understanding the theory and logic behind quantitative methods and analytical techniques and then illustrate how to interpret quantitative methods and corresponding results. The computer assignments contain practical applications of quantitative methods and data analysis.

Assessment and permitted materials

Students’ performance in the course is assessed through two assignments (30% each) and a com-prehensive, final exam (40%).

Minimum requirements and assessment criteria

In total, a minimum of 50 percent is needed to pass the course. The grading system is as follows: 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.
Please note: Policies regarding academic integrity must be followed. Any transgressions will be pun-ished. If issues of academic integrity arise in this course, please talk to the instructor immediately.

Examination topics

The exam covers all topics discussed in the lectures and illustrated and practiced during the assignments.

Reading list

During the tutorials, students will work with a data set that deals with the impact of TV viewing on beauty beliefs and beauty-related behavior and has been used for a paper published in 2007. All participants need to read the following paper by the second session:
Eisend M, Möller J, 2007, The Influence of TV Viewing on Consumers’ Body Images and Related Consumption Behavior, Marketing Letters, 18, 101-116.

It is strongly recommended to refer to further literature such as:
• Diamantopoulos D, Schlegelmilch B, Halkias G., 2023, Taking the Fear out of Data Analysis: Com-pletely Revised, Significantly Extended and Still Fun, 3nd ed., Edward Elgar.
• Hair JF, Black B, Babin B, Anderson RE, 2013, Multivariate Data Analysis. International Edition, 7th ed, Pearson.
• Malhotra N, Nunan D, Birks, DF, 2017, Marketing Research. An Applied Approach, 5th ed, Pear-son.

Association in the course directory

Last modified: Mo 09.09.2024 10:45