DRE 2011 Marketing Models

DRE 2011 Marketing Models

Course code: 
DRE 2011
Department: 
Marketing
Credits: 
6
Course coordinator: 
Rutger Daniel van Oest
Auke Hunneman
Course name in Norwegian: 
Marketing Models
Product category: 
PhD
Portfolio: 
PhD Marketing courses
Semester: 
2017 Autumn
Active status: 
Active
Level of study: 
PhD
Teaching language: 
English
Course type: 
One semester
Introduction

This course is designed to provide an introduction to the area of quantitative marketing models using secondary data. It will give students a fundamental understanding and hands-on experience with commonly used empirical models in business and social science.
 

Learning outcomes - Knowledge

A fundamental understanding and hands-on experience with commonly used empirical models in business and social science. After completion of the seminar, participants should be able to a) understand the conditions under which the various models are appropriate to apply, b) implement these models using statistical software, c) interpret the model outcomes, and d) be able to read quantitative papers in good marketing journals.

Learning outcomes - Skills

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Learning Outcome - Reflection

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Course content

This seminar will discuss a broad range of quantitative models which can be applied to a wide variety of marketing decisions. The model selection reflects the variety of secondary data common in marketing; it distinguishes between individual consumer-level and aggregate sales-level models.

Learning process and requirements to students

Computer-based tools: Standard statistical software and possibly a programming environment.

Software tools
R
SPSS
Additional information

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Qualifications

Enrollment in a PhD programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the course leader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.

Required prerequisite knowledge

It is assumed that every student has basic statistical working knowledge.
 

Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
DRE20112
Grading scale:
ECTS
Grading rules:
Internal and external examiner
Resit:
Examination when next scheduled course
100Yes3 Hour(s)
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Individual
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:Yes
Grouping (size):Individual
Support materials:
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Duration:3 Hour(s)
Comment:
Exam code:DRE20112
Grading scale:ECTS
Resit:Examination when next scheduled course
Exam organisation: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Prepare for teaching
140 Hour(s)
Teaching
30 Hour(s)
Sum workload: 
170

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.