Universität Wien

040501 VO Foundations of Marketing: Data Analysis for Marketing Decisions (MA) (2024S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
MIXED
Moodle

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Details

Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 04.03. 15:00 - 16:30 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 11.03. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 18.03. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 08.04. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 15.04. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 22.04. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 29.04. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 06.05. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 13.05. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Tuesday 21.05. 11:30 - 13:00 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 27.05. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß
  • Monday 03.06. 11:30 - 13:00 Hörsaal 5 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

This course is particularly targeted at students of the Master's in Business Administration, who wish to take "Marketing" as a major or minor, as well as at students of the Master's in International Business Administration, who have chosen "Marketing & International Marketing" in the in-depth phase. Students who wish to write their Master thesis in "Marketing" are strongly encouraged to attend.

This course is also open to students from other programs as well as guest students who meet the study requirements. Note that this course can also be complemented by the UK Repetitorium: Data Analysis for Marketing Decisions in practice (DAMDiP – Course 040213) which trains students in analyzing data with hands-on software applications in the Computer Lab.

Sound knowledge of statistics and data analysis is an important requirement for business practice and marketing decisions – 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, statistical power, effect sizes) and (b) different methods of data analysis (e.g., t-test, χ2 test, AN(C)OVA, regression analysis) in a series of lectures that combine theory with illustrative, practical examples.

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 pro-gram 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.

It is recommended that Erasmus students have successfully completed a basic/introductory marketing course at their home university. DAMD is a prerequisite for the Seminar Marketing.

- The course and any material related to it (lectures, readings, exams, etc) is in English.
- Attendance is not mandatory (yet, highly recommended).
- Students must register to the course to get access to the corresponding Moodle page.
- The course consists of on-site lectures that may be combined with online sessions, if necessary.

More information: https://marketing.univie.ac.at/en/teaching/master/

Assessment and permitted materials

Students’ performance in the course is assessed through a comprehensive, final exam. The exam typically includes questions of different formats (e.g., true-false questions, single-choice questions, and mini cases with multiple-choice questions).

To take the Final Exam, students must register separately for the chosen exam date!

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.

Students can take the exam for maximum 4 times. Additional registration for any exam taken is mandatory.

Examination topics

The final exam covers all topics discussed in the lectures and corresponding book chapters.

Reading list

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)

Association in the course directory

Last modified: We 27.03.2024 11:05