1. Multivariate Analysis Course Outline Daniel Peña 2007/08

2. Contents of the course Multivariate Analysis includes methods for : Data Representation Dimension reduction (PC, Factorial, MDS, AC, CC) Clustering Discrimination

3. Course Outline October 9th: Presentation and Data description October 16th: Data description and graphics October 30th : Principal Components. November 6th: Multidimensional Scaling November 13th : Clustering

4. November 20th: Multivariate Models November 27th: Factorial Models December 4 th : Discriminant Analysis December 11th : Model based clustering and canonical correlation Dcember 18th: Exam

5. Course evaluation 20% classroom participation, 40% project, 40% final exam.

6. References Textbook Peña,D. (2002) Análisis de datos multivariantes, McGraw Hill. (Translated to English and available upon request) Recommended books Cuadras, C.M. (1991), Métodos de Análisis Multivariante, Editorial Universitaria de Barcelona (2ª edición). Dillon, W., Goldstein, M. (1984). Multivariate Analysis. New York, Wiley. Krzanowski, W.J. (1988), Principles of Multivariate Analysis: A. User's Perspective, Oxford University Press, Oxford. *Mardia, K.V., Kent, J.T. y Bibby, J.M. (1979), Multivariate Analysis, New York, Academic Press. Seber, G.A.F. (1984), Multivariate Observations, New York, Wiley.