STATISTICA MULTIVARIATA E RICERCA VALUTATIVA

Course Structure

• TECHNIQUES, MODELS and COMPUTATIONAL PROCEDURES for STATISTICAL ANALYSIS of MULTIDIMENSIONAL DATA

  Lectures. Application of the contents learned to the empirical research issues. Discussion of results.

  
  Seminars on specific topics included in the course.

  Research activity: literature research and data collection.
  
  Data analysis laboratories with training on statistical software.

  Paper presentations on the topics of the course.

• METODOLOGIA DELLA RICERCA VALUTATIVA: APPROCCI, MODELLI E STRUMENTI

  The main objective of the module is to provide the student with the fundamentals of evaluation logic, with particular reference to: the basic elements that characterize the evaluation process, the main evaluation theories; and the impact evaluation approaches, addressing the main methodological issues. Moreover, the module faces in key critical relationships the link between monitoring and evaluation, observing, in particular, the links between monitoring and evaluation indicators. Students will have the opportunity to identify key methodological issues to be considered in implementing monitoring systems effectively oriented to evaluation.

Detailed Course Content

• TECHNIQUES, MODELS and COMPUTATIONAL PROCEDURES for STATISTICAL ANALYSIS of MULTIDIMENSIONAL DATA

  1. Factorial analysis: Principal factors and Principal components - Correspondence analysis: simple and multiple - Multidimensional Scaling - Cluster analysis - Fuzzy clustering methods -
  2. Multiple Regression Models - Log-Linear Models - Non-linear and Logistic Regression Models - Multilevel Models - Structural Equation Models -
  3. In-depth topics: software R Studio

Textbook Information

• TECHNIQUES, MODELS and COMPUTATIONAL PROCEDURES for STATISTICAL ANALYSIS of MULTIDIMENSIONAL DATA

  1. Bartholomew D. J., Steele F., Moustaki I., Galbraith J. I. (2008). Analysis of Multivariate Social Science Data. Boca Raton, FL: CRC Press, Taylor & Francis, pp. 1-144; 175-208.

  for software applications:
  Hahs-Vaughn, D. L. (2017). Applied Multivariate Statistical Concepts. New York, NY: Routledge, pp. 1-56; 335-440
  Digital manuals of the software used.

   

  in Italian to consult if necessary:
  Gallucci M., Leone L., Berlingeri M. (2017), Modelli statistici per le scienze sociali, Pearson, Milano, pp. 323-406 (analisi fattoriale).

  Fabbris L. (1997), Statistica multivariata. Analisi esplorativa dei dati, McGraw-Hill, Milano, pp. 3-77; 301-351 (analisi dei gruppi).

   

  2. Bartholomew D. J., Steele F., Moustaki I., Galbraith J. I., Moustaki I.. (2008). Analysis of Multivariate Social Science Data. Boca Raton, FL: CRC Press, Taylor & Francis, pp. 145-174; 289-362.

  for software applications:
  Hahs-Vaughn, D. L. (2017). Applied Multivariate Statistical Concepts. New York, NY: Routledge, pp. 57-272; 441-570.
  Digital manuals of the software used.

  in Italian to consult if necessary:
  Bohrnstedt G. W. and Knoke D. (1998), Statistica per le scienze sociali, Il Mulino, Bologna, pp. 207-375 (non-linear regression models and logistics).
  Gallucci M., Leone L., Berlingeri M. (2017), Modelli statistici per le scienze sociali, Pearson, Milano, pp. 41-98 (multiple regression models).

   

  3. In-depth topics:

  James Lang & Paul Teetor, R Cookbook, 2nd Edition (https://www.tidytextmining.com/)

  http://www.sthda.com/english/ https://app.rawgraphs.io/
  
  

   

• METODOLOGIA DELLA RICERCA VALUTATIVA: APPROCCI, MODELLI E STRUMENTI

  - Bezzi, C., Cannavò L., Palumbo M. (2010) Costruire indicatori nella Ricerca Sociale e nella Valutazione, Milano, FrancoAngeli: pp. 19-56.
  - Stame N., (2016) Valutazione pluralista. Milano, Franco Angeli, pp 23-111.
  - Stern E. (2016) La valutazione di impatto. Una guida per committenti e manager preparata per Bond. Milano, Franco Angeli, pp 13-65.
  - Mazzeo Rinaldi F., (2012) Il monitoraggio per la valutazione, Milano, FrancoAngeli: pp 17-43 pp 67-115.
  - Stame N. - a cura - (2007) Classici della valutazione. Milano, Franco Angeli, pp. 337-416.