## An Introduction to Applied Multivariate StatisticsSome results on matrices; Multivariate normal distributions; Inference on location - Hotelling's T2; Mutlivariate analysis of variance; Multivariate regression; Analysis of growth curves; Repeated measures and profile analysis; Classification and discrimination; Correlation; Principal component analysis; Factor analysis; Inference on covariance matrices. |

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### Contents

Multivariate Normal Distributions | 25 |

Inference on LocationHotellings T2 | 38 |

Multivariate Analysis of Variance | 96 |

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10 other sections not shown

### Common terms and phrases

analysis of variance assume average Bonferroni calculated canonical variables Chapter chi-square classified column Computational confidence intervals correlation matrix defined degrees of freedom denote diagonal eigenvalues ELYTRA errors of misclassification F-distribution F-statistic F-value factor loadings four given in Table gives H is rejected Hence hypothesis H independently distributed INPUT intraclass correlation length likelihood function likelihood ratio test MANOVA MANOVA H maximum likelihood estimates measurements method monotone sample multiple correlation multivariate normal multivariate normal distribution nonsingular normally distributed Note null hypothesis observations obtain original variables orthogonal orthogonal matrix parameters performed polynomial principal component analysis problem PROC GLM procedure random variables rats regression reject H sample covariance matrix sample mean Section square matrix Srivastava and Khatri SS(TR sum of squares Suppose symmetric Table A.5 test H test statistic test the hypothesis Theorem tillers treatment groups univariate upper al00 wish to test zero