## A Course in Multivariate Analysis |

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### Contents

INTRODUCTION | 5 |

CANONICAL ANALYSIS 88 | 68 |

NOTES ON THE HISTORY OF MULTIVARIATE | 105 |

Copyright | |

2 other sections not shown

### Common terms and phrases

analysis of variance Anderson approximation arises arithmetic Bartlett Berkson's bivariate canonical analysis canonical correlation centroid characteristic equation characteristic roots coefficients column component analysis consider constant corre correlation matrix corresponding covariances criterion degrees of freedom determinantal determined dimensions discriminant function dispersion matrix distri distribution equal error variances estimate Example extract F-distribution factor analysis given gives groups hence hypothesis independent individual largest root latent roots lation Lawley linear function Mahalanobis mathematical maximum likelihood measure method multiple multivariate analysis normal observed obtained ordinary orthogonal parameters parent values principal component principal component analysis problem random variable rank ratio regard regression theory relation require residual sample values Sankhya significant standard Statist sum of squares suppose tion transformation uncorrelated unit variance unity univariate vectors Wilks Wishart distribution