| Area of Matheamtics: | Statistics-Probability-Operational Research (ESPOR) | ||
| Semester: | 8ο | ||
| Course ID: | 82306 | ||
| Course Type: | Elective | ||
| Teaching hours per week: | Theory: 3 | Practice: 0 | Laboratory: 1 |
| ECTS : | 5 | ||
| Eclass: | |||
| Instructors: | |||
Description
- Introduction: Multivariate data: multi-dimensional modeling, quantification of unobserved notions. Multivariate descriptive measures, covariance matrix, generalized variance.
- Graphical representation of multivariate data.
- Multivariate distributions, basic properties. Multivariate normal distribution, properties, estimation. Distributions derived from the multivariate normal distribution.
- Methods of multivariate data analysis: Principal Components Analysis (selection criteria, interpretation of principal components). Principal Components Analysis in sample data. Factor Analysis, orthogonal factor model (estimation, model rotation, interpretation of results, applications). Cluster Analysis: classification (hierarchical and non-hierarchical methods). Discriminant Analysis. Correspondence Analysis. Normal correlation analysis.
- The multivariate linear model, multivariate regression, multivariate analysis.
Bibliography
- Anderson, T. W., An Introduction to Multivariate Statistical Methods, Wiley, 3rd ed., 2003.
- Giri, N. J., Multivariate Statistical Analysis, Marcel Dekker, New York, 2nd ed., 2004.
- Bartholomew D.J., Steele F., Moustaki I., Galbraith J.I., Analysis of Multivariate Social Science Data, Taylor & Fransis, 2008.
