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Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Educational activities
CSimilar or integrative activities
Course completely offered in italian
Course completely offered in english
--Not available
Innovative teaching
The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching.
These CFUs include:
  • Subject taught jointly with companies or organizations
  • Blended Learning & Flipped Classroom
  • Massive Open Online Courses (MOOC)
  • Soft Skills
Course Details
Academic Year 2018/2019
School School of Design
Name (Master of Science degree)(ord. 270) - BV (1162) Communication Design
Track *** - Non diversificato
Programme Year 1

Course Details
ID Code 053791
Course Type Mono-Disciplinary Course
Credits (CFU / ECTS) 6.0
Semester First Semester
Course Description Exploring a multivariate dataset: descriptive statistics and graphical displays. The geometry of a multivariate sample. The distance induced by the covariance matrix. Analysis of covariance structure: principal components and dimensional reduction. Inferences about a mean vector: Hotelling T^2 test. Confidence regions and simultaneous comparisons of component means. Multiple comparisons methods. ANOVA and MANOVA. Discrimination, classification, clustering: Statistical classification: model, miscalassification costs and prior probability. Bayesian supervised classification and the Fisher approach to discriminant analysis. Alternative approaches to classification: logistic regression, CART. Similarity measures. Unsupervised classification; hierarchical and nonhierarchical methods. Multidimensional scaling. Functional data Analysis: smoothing and representing functional data. Dimensional reduction: functional principal components. Allignment of functional data: amplitude and phase variability. Registration procedures. Classiffication with functional data. Mixed effects models: introduction to linear and generalized multilevel models. Multivariate logistic regression models for binary data: classification and prediction. Multilevel models for longitudinal data. Growth curves with autocorrelated residuals. Models for multivariate repente measures. Introduction to statistical models for the analysis of spatial data.
Scientific-Disciplinary Sector (SSD)
Educational activities SSD Code SSD Description CFU
Innovative teaching The course includes  1.0  credits in Innovative Teaching as follows:
  • Blended Learning & Flipped Classroom

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--AZZZZSecchi Piercesare
manifesti v. 3.5.17 / 3.5.17
Area Servizi ICT