Checking date: 03/04/2018


Course: 2019/2020

Multivariate Data Analysis
(16247)
Master in Marketing (Plan: 279 - Estudio: 269)
EPE


Coordinating teacher: KAISER REMIRO, REGINA

Department assigned to the subject: Statistics Department

Type: Electives
ECTS Credits: 3.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Not required.
Objectives
Skills to be acquired General skills *CG2: Effective knowledge of other disciplines / techniques used in Marketing and Market Research. Specific skills: *CE5: To understand and use statistics and econometrics tools to analyze data and marketing problems through scientific models, using appropriate software. Learning objectives: ¿ Understand basic foundations of multivariate data analysis. ¿ Apply fundamental principles and methods of multivariate data analysis to a wide range of problems. ¿ Design, correctly implement and document solutions to the ¿real-world¿ problems.
Description of contents: programme
Introduction to multivariate data analysis. Principal component analysis. Factor analysis. Correspondence analysis Discriminant analysis and classification Cluster analysis Multidimensional scaling. Structural (Simultaneous equation) models with latent variables PLS Data mining
Learning activities and methodology
Classes may involve lectures, small group exercises, case analyses and discussions. The lectures will serve to establish the conceptual foundations. Practical classes are designed so that students can develop skills and abilities required properly established. Student contributions are an important part of the course. Students are expected to read assigned materials for each class; attend class, participate and contribute to discussions.
Assessment System
  • % end-of-term-examination 40
  • % of continuous assessment (assigments, laboratory, practicals...) 60

Basic Bibliography
  • Dillon, W., Goldstein, M. . Multivariate Analysis. . New York, Wiley. 1984

The course syllabus may change due academic events or other reasons.