2002Wiley series in probability and statisticsRequires access

Introduction

Alvin C. Rencher

Open publisher page 1 citations

Abstract

This is a brief introductory chapter. Various types of multivariate data are described and illustrated. Some sources of multivariate data are the sciences, humanities, business, medical fields, etc. Most multivariate data sets involve correlated variables, for which there are many useful multivariate exploratory techniques as well as inferential procedures. Many multivariate techniques are extensions of univariate procedures. The univariate procedures are reviewed in the text. Other multivariate techniques have no univariate analog. The objectives for the readers of the book are (1) understand the details of various multivariate techniques, (2) be able to select one or more multivariate procedures for a given multivariate data set, and (3) interpret the results of a computer analysis of a multivariate data set. Various types of data and accompanying analyses are described. Throughout the book there are many examples and problems involving real data sets. Answers to most problems are provided in Appendix B.

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This is a brief introductory chapter. Various types of multivariate data are described and illustrated. Some sources of multivariate data are the sciences, humanities, business, medical fields, etc. Most multivariate data sets involve correlated variables, for which there are many useful multivariate exploratory techniques as well as inferential procedures. Many multivariate techniques are extensions of univariate procedures. The univariate procedures are reviewed in the text. Other multivariate techniques have no univariate analog. The objectives for the readers of the book are (1) understand the details of various multivariate techniques, (2) be able to select one or more multivariate procedures for a given multivariate data set, and (3) interpret the results of a computer analysis of a multivariate data set. Various types of data and accompanying analyses are described. Throughout the book there are many examples and problems involving real data sets. Answers to most problems are provided in Appendix B.

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Available abstract

This is a brief introductory chapter. Various types of multivariate data are described and illustrated. Some sources of multivariate data are the sciences, humanities, business, medical fields, etc. Most multivariate data sets involve correlated variables, for which there are many useful multivariate exploratory techniques as well as inferential procedures. Many multivariate techniques are extensions of univariate procedures. The univariate procedures are reviewed in the text. Other multivariate techniques have no univariate analog. The objectives for the readers of the book are (1) understand the details of various multivariate techniques, (2) be able to select one or more multivariate procedures for a given multivariate data set, and (3) interpret the results of a computer analysis of a multivariate data set. Various types of data and accompanying analyses are described. Throughout the book there are many examples and problems involving real data sets. Answers to most problems are provided in Appendix B.

Key concepts: Multivariate statistics, Univariate, Multivariate analysis, Set (abstract data type), Computer science, Data set, Exploratory data analysis, Data mining

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