Università Roma Tre

The first lessons will be devoted to a summary of basic statistical concepts (such as variance, covariance, correlation, linear combinations) and matrix algebra.
We will then move on to the study of possible data matrix syntheses: composite indicators, principal component analysis; cluster analysis.
Finally, after a summary of simple regression (i.e. the straight line), we will move on to the study of multiple regression.
Emphasis will be placed on case studies .

Open issues in composite indicators. Terzi, Otoiu, Mazziotta, Pareto, Grimaccia. Downloadable from Roma TrE-press
https://romatrepress.uniroma3.it/wp-content/uploads/2021/03/open-togmp-2.pdf

B.F.J. Manly and J.A. Navarro Alberto. Multivariate Statistical Methods: A Primer, Fourth Edition. Taylor & Francis (2016)