Description
Book SynopsisAn insightful guide to understanding and visualizing multivariate statistics using SAS, STATA, and SPSS
Multivariate Analysis for the Biobehavioral and Social Sciences: A Graphical Approach outlines the essential multivariate methods for understanding data in the social and biobehavioral sciences. Using real-world data and the latest software applications, the book addresses the topic in a comprehensible and hands-on manner, making complex mathematical concepts accessible to readers.
The authors promote the importance of clear, well-designed graphics in the scientific process, with visual representations accompanying the presented classical multivariate statistical methods . The book begins with a preparatory review of univariate statistical methods recast in matrix notation, followed by an accessible introduction to matrix algebra. Subsequent chapters explore fundamental multivariate methods and related key concepts, including:
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Factor analysis and related m
Table of Contents
PREFACE xiii
1 OVERVIEW OF MULTIVARIATE AND REGRESSION METHODS 1
2 THE SEVEN HABITS OF HIGHLY EFFECTIVE QUANTS: A REVIEW OF ELEMENTARY STATISTICS USING MATRIX ALGEBRA 20
3 FUNDAMENTALS OF MATRIX ALGEBRA 88
4 FACTOR ANALYSIS AND RELATED METHODS: QUINTESSENTIALLY MULTIVARIATE 139
5 MULTIVARIATE GRAPHICS 227
6 CANONICAL CORRELATION: THE UNDERUSED METHOD 283
7 HOTELLING’S T 2 AS THE SIMPLEST CASE OF MULTIVARIATE INFERENCE 333
8 MULTIVARIATE ANALYSIS OF VARIANCE 351
9 MULTIPLE REGRESSION AND THE GENERAL LINEAR MODEL 373
APPENDICES: STATISTICAL TABLES 443
NAME INDEX 456
SUBJECT INDEX 460
