2025
Methods of Multivariate Statistics
Name: Methods of Multivariate Statistics
Code: MAT12612D
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Mathematics
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
The purpose of this course is to prepare students for multivariate data analysis, through the learning of multivariate dependence and interdependence statistical thecniques, and using apropriate software to deal with multivariate statistical approaches , data type and objectives. In particular, the students should be able to determine which multivariate technique is appropriate for a specific research problem and should be able to obtain knowledge about:
- Multivariate interdependence techniques
- Exploratory analyses of multivariate data (qualitative and quantitative)
- Multivariate dependence thechniques
- Multivariate interdependence techniques
- Exploratory analyses of multivariate data (qualitative and quantitative)
- Multivariate dependence thechniques
Contents
1. Multivariate Statistical Methods: an introduction. Concepts.
2. Multivariate data examination.
3. Multivariate dependence techniques (multiple linear regression, discriminant analysis, multivariate variance analysis and other topics) and multivariate interdependence techniques (Cluster analysis, exploratory factor analysis, confirmatory factor analysis and other topics).
4. An introduction to structural equation modeling (SEM).
2. Multivariate data examination.
3. Multivariate dependence techniques (multiple linear regression, discriminant analysis, multivariate variance analysis and other topics) and multivariate interdependence techniques (Cluster analysis, exploratory factor analysis, confirmatory factor analysis and other topics).
4. An introduction to structural equation modeling (SEM).
Teaching Methods
In order to reach higher levels of school success, the classes combine the teaching of concepts with their application to particular examples. The presentation of the theoretical component of the program should motivate students to learn and explore using appropriate statistical software, which are chosen according to their suitability to the objectives outlined and to the existing conditions.
In terms of evaluation, the student may choose between final exam and continuous form, through the presentation of scientific works/ reports.
In terms of evaluation, the student may choose between final exam and continuous form, through the presentation of scientific works/ reports.
Accreditations and Certifications
