Syllabus

Title
0752 Retail Marketing 1 (RM 1)
Instructors
ao.Univ.Prof. Dr. Andreas Mild, Dr. Martin Waitz
Contact details
martin.waitz@wu.ac.at, andreas.mild@wu.ac.at
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/23/19 to 09/27/19
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Course I - Retail Marketing
Dates
Day Date Time Room
Thursday 10/03/19 01:30 PM - 05:00 PM D2.0.038
Thursday 10/10/19 01:30 PM - 05:00 PM D2.0.038
Thursday 10/17/19 01:30 PM - 05:00 PM D2.0.038
Thursday 10/24/19 01:30 PM - 05:00 PM D2.0.038
Thursday 11/07/19 01:30 PM - 05:00 PM D2.0.038
Thursday 11/14/19 01:30 PM - 05:00 PM D2.0.038
Thursday 11/21/19 01:30 PM - 05:00 PM TC.2.03

On this page:

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Contents
The course gives an introduction into Marketing Research and Analytics with an emphasis on problems in Retailing. All analyses will be done using R. In this part of the course, a general introduction into R and fundamentals of Data Analysis will be covered. 
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Learning outcomes
After completing this course students will have a basic knowledge of fundamentals of Data Analysis for Marketing problems. They are able to describe and visualize data with R and apply models for advanced marketing applications.  Students will learn about decision problems in retailing like pricing, assortment or advertising planning. Beside an understanding of the problem structure, students will learn to apply mathematical and statistical tools to support decision making. Apart from that, completing this course will contribute to the students’ ability to efficiently work and communicate in a team, work on solutions for complex practical problems by using modern statistical software.
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Attendance requirements

According to the examination regulation full attendance is intended for a PI. Absence in one unit is tolerated if a proper reason is given.

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Teaching/learning method(s)
The course will combine alternative ways to deliver the different topics to the students. On the one hand, a classical lecture style approach where the instructor presents the software will be used; on the other hand, students will have to solve hand on problems in class and as homework.
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Assessment

The final grade of the course will depend on

 

  • final oral exam (60%)
  • homework assignments (40%)

 

Please note that there will be no possibility to retake the final exam. The assessment of the homework assignments is based on a regular grading scheme that is indicated with the sample problems.

 

Grading scale:

(1) Excellent: 90% - 100%

(2) Good: 80% - <90%

(3) Satisfactory: 70% - <80%

(4) Sufficient: 60% - <70%

(5) Fail: <60%

Prerequisite for passing the course: minimum performance of 40% in the final examination.

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Prerequisites for participation and waiting lists

Class attendance in all sessions is mandatory!

General prerequisites:

  • Basic knowledge in statistics
  • Basic knowledge in R
  • Basic knowledge in operations management

Incoming students (exchange partners): min. 5 ECTS credits in  Operations Research

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Readings
1 Author: Chapman/MCDonnell Feit
Title: R for Marketing Research and Analytics

Publisher: Springer
Year: 2015
Content relevant for class examination: Yes
Recommendation: Essential reading for all students
Type: Book
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Availability of lecturer(s)

martin.waitz@wu.ac.at

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Other
program's website: www.wu.ac.at/master/scm
Last edited: 2019-04-02



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