Quantitative Methods for Marketing - Explanatory Methods
Objectives
1. Develop and interpret the results of multiple regression analysis;
2. Develop and interpret the results of regression models for categorical dependent variables (probit/logit);
3. Develop and interpret the conjoint analysis;
4. Develop and interpret the results of multiple regression analysis based on principal components;
5. Develop and interpret the results of structural equation models (SEM).
General characterization
Code
200093
Credits
7.5
Responsible teacher
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
Recommended: Quantitative methods for marketing - descriptive methods
Bibliography
Hair, J. F., Tatham, R. L., Anderson, R. E., & Black, W. (2010). Multivariate data analysis. Seventh edition, Upper Saddle River, NJ: Pearson Prentice Hall.; Hair, J. F., Hult G.T., Ringle C.M., & Sartedt M. (2014) A primer on partial least squares structural equation modeling (PLS-SEM).; Long J. S. (1997). Regression Models for Categirical and limited Dependemt Variables: Sage Publications.; Sharma, S., (1996) Applied Multivariate Techniques, John Wiley & Sons.; Vilares, J. M. & Coelho P. S. (2005) Satisfação e Lealdade do Cliente: Metodologias de avaliação, Gestão e Análise. Lisboa: Escolar Editora.
Teaching method
The course is based on theoretical lessons (presentation of concepts, methodologies), followed by lessons for case problems solving (applying techniques and discussing results).
Evaluation method
Final exam (50%) + Project with oral presentation (50%).
Subject matter
1. Multiple regression analysis;
2. Regression models for categorical dependent variables (probit/logit);
3. Conjoint analysis;
4. Multiple regression analysis based on principal components;
5. Structural equation models (SEM).