Foto del docente

Silvia Cagnone

Associate Professor

Department of Statistical Sciences "Paolo Fortunati"

Academic discipline: SECS-S/01 Statistics

Curriculum vitae

Actual position: Associate Professor in Statistics, Department of Statistics, University of Bologna.

Academic degrees

  • 2014 Associate Professor,  Department of Statistics, University of Bologna.

  • 2006  Lecturer in Statistics, Department of Statistics, University of Bologna.

  • 2003   Postdoctoral Fellow, Department of Statistics, University of Bologna. Research topic: “Generalized latent variable models: methodological developments and applied aspects”, supervisor prof. Stefania Mignani.

  • 2003   PhD in Statistics, Department of Statistics, University of Bologna. Thesis: “Latent Variable Models for Ordinal Data”, tutor, prof. Stefania Mignani, topic, Methodological Statistics

  • 1999   Degree in Statistics,  Department of Statistics,University of Bologna. Thesis: “The quality of the front-office in the University services: a model of analysis”, advisor prof. Gian Luca Marzocchi, topic Marketing.

 

Institutional responsabilities

  • 2018- Delegate of the International Relations for the Department of Statistical Sciences, Univeristy of Bologna.
  • 2017- Deputy Director of the P.hD. programme in Statistics, Department of Statistical Sciences, University of Bologna.
  • 2013- Member of the Board of the Ph.D. programme in Statistics , Department of Statistical Sciences, University of Bologna.


Visiting positions

  • 2006 Visiting Scholar, Statistics Department, Athens University of Economicsand Business, Athens (May). Supervisor: prof. Irini Moustaki.

  •  2005 Visiting Scholar, Statistics Department, Athens University of Economics and Business, Athens (April- June). Supervisor: prof. Irini Moustaki.
  • 2001 Visiting Student, Statistics Department, London School of Economics and Political Science, London (April-July). Supervisor: prof. Irini Moustaki

Teaching
Teaching courses concern methodological statistics and are Inferential Statistics, Data analysis and Evaluation models.

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