Universität Wien FIND

040501 VO Foundations of Marketing: Data Analysis for Marketing Decisions (MA) (2023S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften

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. 60 participants
Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

Friday 03.03. 09:45 - 11:15 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Monday 06.03. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Friday 10.03. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Tuesday 14.03. 16:45 - 18:15 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 20.03. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 27.03. 09:45 - 11:15 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Friday 31.03. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Monday 17.04. 13:15 - 14:45 Hörsaal 6 Oskar-Morgenstern-Platz 1 1.Stock
Thursday 20.04. 13:15 - 14:45 Hörsaal 4 Oskar-Morgenstern-Platz 1 Erdgeschoß
Tuesday 02.05. 15:00 - 16:30 Hörsaal 14 Oskar-Morgenstern-Platz 1 2.Stock
Monday 08.05. 15:00 - 16:30 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß
Wednesday 10.05. 13:15 - 14:45 Hörsaal 1 Oskar-Morgenstern-Platz 1 Erdgeschoß

Information

Aims, contents and method of the course

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 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.

Assessment and permitted materials

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.

Minimum requirements and assessment criteria

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.

Examination topics

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).

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 19.04.2023 10:08