MULTIVARIATE STATISTICS
Academic year and teacher
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- Versione italiana
- Academic year
- 2018/2019
- Teacher
- VALENTINA MINI
- Credits
- 6
- Didactic period
- Primo Semestre
- SSD
- MAT/06
Training objectives
- Knowledge of theoretical bases and understanding of methodological developments related to multidimensional data analysis. Familiarity and autonomy in the application of the main multivariate methods using R.
Prerequisites
- Linear algebra.
Course programme
- Overview (introduction) [2h]; Vectors and Matrices [3h]; Regression Analysis. Linear Regression and multivariate regression: theory, applications and lab using R [10h]; Analysis of Interdependence: tecniques, intuition and applications using R [16h]; Analysis of Dependence: overview [3h]; Tests [6h]; Final Exercises [2h].
Didactic methods
- Frontal lectures, exercises and lab using R
Learning assessment procedures
- Final written test based on three sections:
- theory (multiple choice)
- applied multivariate statistics (multiple choice)
- exercise based on free software R (the students should write the R script required to conduct the analysis) Reference texts
- Slides of the course, suggested book and articles, exercises. R guide and tutorial.
