title: Fuzzy Analysis of Students' Ratings.
abstract: Intuitionistic fuzzy sets (IFS) represent a methodology for quantifying latent variables in questionnaire analysis through membership and non-membership functions, which are linked by an uncertainty function.
  
  
  
  We aim to apply an IFS approach to the problem of students' satisfaction of university teaching. Such framework can take into account a source of uncertainty related to items and another related to subjects.
  
  
  
  A new technique for IFS analysis is set forth and generalized to a multivariate scenario. Potential advantages of the IFS perspective with respect to other nonfuzzy approaches are provided.
  
  
  
  We apply this method to a national program of university courses evaluation and we focus, in particular, on the outcomes of two Masters in Statistics.
authors: Department of Economics, Management and Statistics, Statistical Section, University of Milan-Bicocca, Milano, Italy.
authors: Donata
authors: D
authors: Marasini
authors: Department of Economics, Management and Statistics, Statistical Section, University of Milan-Bicocca, Milano, Italy.
authors: Piero
authors: P
authors: Quatto
authors: Department of Economics, Management and Statistics, Statistical Section, University of Milan-Bicocca, Milano, Italy enrico.ripamonti@unimib.it.
authors: Enrico
authors: E
authors: Ripamonti
mesh_terms: D000328:Adult; D005060:Europe; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D008297:Male; D010549:Personal Satisfaction; D013223:Statistics as Topic / Q000193:education*; D013334:Students / Q000706:statistics & numerical data; D013663:Teaching / Q000458:organization & administration*; D014495:Universities / Q000458:organization & administration*; D055815:Young Adult
keywords: fuzzy sets; intuitionistic fuzzy sets; multivariate analysis; satisfaction; teaching evaluation