1. Capacity for identifying problems associated with statistical data in several variables.
2. Basic knowledge for handling vectors and matrices.
3. Acquire skills in multivariate data description.
4. Capacity for making and interpreting plots of multivariate datasets.
5. Know the properties of multivariate distributions.
6. Capacity for making hypotesis testing on a multivariate population.
7. Acquire skills in principal component analysis and factorial analysis.
8. Acquire skills in heterogeneity problems such as outlier detection, hypothesis testing for different means, classification and clustering.
9. Handle statistical software for multivariate analysis.
1. Aptitude to understand a real problem and to analyze it as an statistical problem.
2. Modeling and solving problems.
3. Capacity of analysis and synthesis.
4. Oral and written skills.
5. Aptitude to work in a group.