Universidade Nova de Lisboa

Universidade Nova de Lisboa

NOVA Information Management School

Quantitative Methods for Marketing - explanatory methods

Code

200093

Academic unit

NOVA Information Management School

Credits

7.5

Teacher in charge

Weekly hours

2.0

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

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).

Prerequisites

Recommended: Quantitative methods for marketing - descriptive methods

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).

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.
Sharma, S., (1996) Applied Multivariate Techniques, John Wiley & Sons.

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%).

Courses