Multivariate Statistics

Syllabus: 

Random Vectors. Mean vectors and Covariance and Correlation Matrices. Multivariate Normal Distribution. Principal component analysis. Factor analysis. Analysis of Conglomerates or Clusters. Multidimensional scaling. Discriminant Analysis. Canonical Analysis. Correspondence Analysis.

Bibliography

Mandatory: 

•    Johnson, R. A., Wichern, D. W. (1998). Applied multivariate statistical analysis. 4th ed. New Jersey. Prentice Itall Inc.
•    Lattin, James. Multivariate Data Analysis. Cengage Learning.
•    Joseph F. Hair, Jr et al (2009). Multivariate analysis of data. Bookman.

Complementary: 

•    Anderson, T. W (1984). An introduction to multivariate statistical analysis. Wiley, 1984.
•    Gujarati, D., Porter, D.C. (2011). Basic Econometrics. Bookman, 2011.
•    Krzanowski, W. J., Marriott, F. H. C. (1995). Multivariate analysis. Arnold.
•    Adriana Rodrigues et al. (2007). Multivariate analysis for administration, accounting and economics courses. Atlas.
•    Rencher, Alvin C. (1995). Methods of multivariate analysis. Wiley