Raffaella Piccarreta

Raffaella Piccarreta

Decision Sciences and Business Analytics

raffaella.piccarreta@unibocconi.it

via Roentgen 1 - Piano III - Stanza D1-09
Tel.+39 02 5836 5659 Fax.+39 02 5836 5630

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Curriculum Vitae

Degree in Economics and Social Sciences from Università Bocconi. 

PhD in Statistics from the Università di Trento.

 

Academic position and/or Professional activities

Associate Professor of Decision Sciences

At Università Bocconi she has taught Statistics, Computing, Applied Economics, Economic Statistics, Sample Surveys, Statistics for Ecoomics and Business (EMIT, LS), Data Analysis (PhD in Business Administration and Management, PhD in Statistics). She taught Statistics and economic statistics at the Faculty of Economics, Università dell’Insubria, and Statistics at the Faculty of Political Science, Università Cattolica del Sacro Cuore.

She visited CSSS (Center for Statistics and the Social Science), University of Washington, Seattle, USA, from September 2008 to December 2008, and the Dept. of Social Science Research Methods, Faculty of Social Sciences, Vrije Universiteit Amsterdam from September 2007 to December 2007.

She was a referee for the following journals: Journal of the Royal Statistical Society, Series A, Statistics and Computing, Computational Statistics, Journal of Applied Statistics, Statistical Papers, Sociological Methods and Research, Statistics in Medicine, Sociological Methods, Statistical Methods and Applications, Advances in Life Course Research, Advances in Data Analysis and Classification, Journal of Statistical Software, Statistical Methods and Applications

She is a member of the Società Italiana di Statistica (SIS). She is fellow of 'Carlo F. Dondena' Centre for Research on Social Dynamics.

She obtained the award Indennità di eccellenza nella ricerca, Bocconi University (academic years 2008 and 2009).

 

Research Interests

  • Multivariate data analysis
  • Categorical data analysis
  • Sequence Analysis
  • Classification and Regression trees (for ordinal response variables)
  • Analysis of Dissimilarity matrices
  • Genetic algorithms
  • Neural networks