DRE 2011 Marketing Models

DRE 2011 Marketing Models

Course code: 
DRE 2011
Department: 
Marketing
Credits: 
6
Course coordinator: 
Rutger Daniel van Oest
Auke Hunneman
Product category: 
PhD
Portfolio: 
PhD Marketing courses
Semester: 
2019 Autumn
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

This course is designed to provide an introduction to econometric models for the analysis of secondary data sources containing marketing actions and outcomes. It will give students a fundamental understanding and hands-on experience with commonly used empirical models in marketing in particular, and business and social science in general.

Learning outcomes - Knowledge

A fundamental understanding of commonly used empirical models in marketing applications in particular, and business and social science in general. This includes linear regression, binary logit, conditional logit, nested logit, Poisson regression, latent classes, hierarchical linear models, and spatial models.  

After completion of the seminar, participants should be able to understand the properties of these models and the conditions under which the various models are appropriate to apply,

Learning outcomes - Skills

Being able to implement (or code up) the models using statistical software and interpret the model outcomes.

General Competence

Being able to read and appreciate quantitative (econometric) papers in the good marketing journals.

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.

Teaching and learning activities

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

Software tools
R
SPSS
Additional information

-

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
Type of Assessment: 
Ordinary examination
Total weight: 
100
Workload activityDurationType of durationComment student effort
Prepare for teaching140Hour(s)
Teaching30Hour(s)
Expected student effort:
Workload activity:Prepare for teaching
Duration:140 Hour(s)
Comment:
Workload activity:Teaching
Duration:30 Hour(s)
Comment:
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.