2025
Multivariate Data Analysis
Name: Multivariate Data Analysis
Code: MAT13613M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Mathematics
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Regime de Frequência: Presencial
Sustainable Development Goals
Learning Goals
The main objective of the curricular unit is to provide students with tools and silks necessary in multivariate quantitative research, including inferential methods for dealing with uncertainties in drawing conclusions from multivariate collected data. At the conclusion of the course it is expected that students will be able to specify conceptualized models and to deal with theoretical issues related with dependent, interdependent and extensions multivariate statistical techniques using adequate statistical packages (SPSS/EXCEL/AMOS/R...). Students will also be prepared to critique results reported in scientific literature.
All the techniques will be accomplished with the resolution of exercises related with scientific areas of interest.
All the techniques will be accomplished with the resolution of exercises related with scientific areas of interest.
Contents
1. Overview of Multivariate Statistical Methods. Introduction. Dependence Techniques and Interdependence Techniques. Extentions.
2. Preliminary and exploratory multivariate data analysis
3. Principal Component Analysis
4. Exploratory Factorial Analysis versus Confirmatory Factorial Analysis
5. Cluster Analysis
6. Structural Equation Modeling: an introduction
2. Preliminary and exploratory multivariate data analysis
3. Principal Component Analysis
4. Exploratory Factorial Analysis versus Confirmatory Factorial Analysis
5. Cluster Analysis
6. Structural Equation Modeling: an introduction
Teaching Methods
The methodology incorporates several innovative strategies for enhancing student motivation and performance. Learning techniques, such as the use of hands-on activities and cooperative learning assignments, are preferred, as they allow students to construct their own understanding of statistical concepts and applications by actively engaging the course material (projection of slides about statistical theory followed by the resolution of exercises). For each activity, it is also provided a summary of the critical procedural steps and a list of materials needed.
Assessment
During the regular assessment period, students can choose between one of two assessment methods: continuous or final.
Students should prioritize the continuous assessment method, taking at least two individual mini-tests with restricted consultation. The grade for the course will be obtained by calculating the arithmetic mean (rounded to the nearest whole number) of the grades obtained in each of the mini-tests. If students opt for the final assessment method, they will have to take an exam covering all the course content.
In other assessment periods (resit/Appeals, special, or extraordinary), students are assessed using the final assessment method, taking an exam covering all the course content.
Both assessment systems (continuous or final) are in accordance with the Academic Regulations of the University of Évora, and a student passes the course if they obtain a grade equal to or higher than 9.5 out of 20.
Students should prioritize the continuous assessment method, taking at least two individual mini-tests with restricted consultation. The grade for the course will be obtained by calculating the arithmetic mean (rounded to the nearest whole number) of the grades obtained in each of the mini-tests. If students opt for the final assessment method, they will have to take an exam covering all the course content.
In other assessment periods (resit/Appeals, special, or extraordinary), students are assessed using the final assessment method, taking an exam covering all the course content.
Both assessment systems (continuous or final) are in accordance with the Academic Regulations of the University of Évora, and a student passes the course if they obtain a grade equal to or higher than 9.5 out of 20.
Teaching Staff
- Luís Miguel Lindinho da Cunha Mendes Grilo [responsible]
