Predictive Analytics in Marketing
Objectives
- Develop and interpret the results of multiple regression analysis;
- Develop and interpret the conjoint analysis;
- Develop and interpret the results of regression models for categorical dependent variables (probit/logit);
- Develop and interpret the results of multiple regression analysis based on factors;
- Develop and interpret the results of structural equation models (SEM).
General characterization
Code
200190
Credits
7.5
Responsible teacher
Tiago André Pereira Branco
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
NA
Bibliography
Teaching method
The curricular unit is based on mix of theoretical lectures and practical classes. Each session will introduce new concepts, as well as the applications of the learned concepts through practical exercises and using different computational tools. Different learning strategies will be used, such as lectures, slide show demonstrations, step-by-step tutorials on how to approach practical examples, questions, and answers.
Evaluation method
1st Period
Master students: Project (group with 4 students) with oral presentation (50%), participation and discussion (10%), and exam (40%).
Ph.D. students: Scientific paper (8000 words maximum) as individual work (90%), participation and discussion (10%).
2nd Period
Master students: Project (group with 4 students) with oral presentation (50%), and exam (50%).
Ph.D. students: Scientific paper (8000 words maximum) as individual work (100%).
Project/Scientific paper:
- Practical/scientific work with own data (application of at least one technique taught in the course);
- Presentation of a proposal until March 7th of 2023 (one page);
- Project status display until April 11th of 2023 (one page);
- Project status display until day June 6th of 2023 (maximum 5 page);
- Discussion with the group (4 elements) for project;
- Date of presentations to be arranged;
- All group´s members need to be present;
- Maximum 15 minutes;
- Maximum 4000 words for project and 8000 words for scientific paper.
Subject matter
1. Hypotheses testing
2. Multiple regression analysis
3. Regression models for categorical dependent variables (probit/logit)
4. Multiple regression analysis based on factors
5. Structural equation models (SEM)
Programs
Programs where the course is taught:
- Specialization in Data Science for Marketing
- Specialization in Digital Marketing and Analytics
- Specialization in Marketing Intelligence
- Specialization in Marketing Research and CRM
- Laboral - Especialização em Data Science for Marketing
- Specialization in Digital Marketing and Analytics
- Specialization in Marketing Intelligence
- Master Degree in Data Driven Marketing
- PostGraduate in Data Science for Marketing
- PostGraduate Digital Marketing and Analytics
- PostGraduate Marketing Research e CRM
- PostGraduate in Marketing Intelligence
- PostGraduate in Enterprise Information Systems