MUNI SHANKER SRIVASTAVA, PhD, is a Professor in the Department of Statistics at the University of Toronto. He is an Elected Member of the International Statistics Institute, a Fellow of the Institute of Mathematical Statistics, a Fellow of the Royal Statistical Society, and a Fellow of the American Statistical Association.

"...an excellent book...one of the best references for its level." (Technometrics, Vol. 45, No. 1, February 2003) "...a very useful, well-written, and interesting book...an excellent book; highly recommended." (Choice, Vol. 40, No. 5, January 2003)

• Abbreviations and Notations. Preface.Multivariate Methods: An Overview.Multivariate Normal Distributions.Outliers Detection and Normality Check.Inference on Location—Hotelling's T2.Repeated Measures.Multivariate Analysis of Variance.Profile Analysis.Classification and Discrimination.Multivariate Regression.Growth Curve Models.Principal Component Analysis.Factor Analysis.Inference on Covariance Matrices.Correlations.Missing Observations: General Case.Missing Observations: Monotone Sample.Bootstrapping.Imputting Missing Data.Some Results on Matrices.Tables.Bibliography.

MUNI SHANKER SRIVASTAVA, PhD, is a Professor in the Department of Statistics at the University of Toronto. He is an Elected Member of the International Statistics Institute, a Fellow of the Institute of Mathematical Statistics, a Fellow of the Royal Statistical Society, and a Fellow of the American Statistical Association.

"...an excellent book...one of the best references for its level." (Technometrics, Vol. 45, No. 1, February 2003) "...a very useful, well-written, and interesting book...an excellent book; highly recommended." (Choice, Vol. 40, No. 5, January 2003)

• Abbreviations and Notations. Preface.Multivariate Methods: An Overview.Multivariate Normal Distributions.Outliers Detection and Normality Check.Inference on Location—Hotelling's T2.Repeated Measures.Multivariate Analysis of Variance.Profile Analysis.Classification and Discrimination.Multivariate Regression.Growth Curve Models.Principal Component Analysis.Factor Analysis.Inference on Covariance Matrices.Correlations.Missing Observations: General Case.Missing Observations: Monotone Sample.Bootstrapping.Imputting Missing Data.Some Results on Matrices.Tables.Bibliography.

MUNI SHANKER SRIVASTAVA, PhD, is a Professor in the Department of Statistics at the University of Toronto. He is an Elected Member of the International Statistics Institute, a Fellow of the Institute of Mathematical Statistics, a Fellow of the Royal Statistical Society, and a Fellow of the American Statistical Association.

"...an excellent book...one of the best references for its level." (Technometrics, Vol. 45, No. 1, February 2003) "...a very useful, well-written, and interesting book...an excellent book; highly recommended." (Choice, Vol. 40, No. 5, January 2003)

• Abbreviations and Notations. Preface.Multivariate Methods: An Overview.Multivariate Normal Distributions.Outliers Detection and Normality Check.Inference on Location—Hotelling's T2.Repeated Measures.Multivariate Analysis of Variance.Profile Analysis.Classification and Discrimination.Multivariate Regression.Growth Curve Models.Principal Component Analysis.Factor Analysis.Inference on Covariance Matrices.Correlations.Missing Observations: General Case.Missing Observations: Monotone Sample.Bootstrapping.Imputting Missing Data.Some Results on Matrices.Tables.Bibliography.