## Applied Multivariate Statistical AnalysisThis market leading text is appropriate for courses that teach statistical methods for describing and analyzing multivariate data in depts. of statistics, math, marketing, and in the biological, physical, and social sciences. The 4th edition makes more extensive use of SAS and SPSS output with an emphasis on interpretation. Features include additional exercises, data sets, and graphics to illustrate points. Various techniques such as MANOVA and Discriminate Analysis, Correspondence Analysis, and Biplots are integrated more thoroughly. |

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### Contents

Concepts | 86 |

SAMPLE GEOMETRY AND RANDOM SAMPLING | 116 |

THE MULTIVARIATE NORMAL DISTRIBUTION | 157 |

Copyright | |

12 other sections not shown

### Common terms and phrases

approximation axes bivariate normal Bonferroni calculate canonical correlations canonical variates Chernoff faces chi-square cluster columns confidence intervals Consider Construct coordinates correlation coefficient corresponding cross products data matrix determined dimensions eigenvalues eigenvectors ellipse ellipsoid equal equation error rate Example Exercise factor analysis factor loadings factor model factor scores Figure function given independent interpretation large sample least squares length linear combinations linkage MANOVA maximum likelihood estimates measurements methods misclassification multivariate normal normal distribution normal populations observations obtained orthogonal outliers pairs parameters points positive definite prediction prior probabilities procedure profiles Q-Q plot random sample random variables random vector regression model reject H0 residual response Result ri ri ri rotated sample canonical sample covariance matrix sample mean sample principal components sample variance scatter plot simultaneous confidence intervals squared distance standardized statistical distance sum of squares tion treatment univariate values zero