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Matrix Algebra, Sample Geometry, and the Multivariate Normal Distribution.
by Richard A. Johnson and Dean W. Wichern remains a cornerstone textbook for experimental scientists, graduate students, and data practitioners seeking a rigorous yet accessible introduction to managing complex datasets.
Inferences about Mean Vectors, Comparisons of Several Means (MANOVA), and Multivariate Linear Regression.
Features numerous real-world data sets and exercises, often including snapshots of corresponding SAS output to bridge theory and practice.
The 6th edition is organized into four main parts, covering everything from fundamental matrix algebra to advanced grouping techniques. Key Chapters & Concepts I. Getting Started
The primary goal of this market-leading text is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. It is designed for students who have completed at least two prior statistics courses and assumes a basic comfort level with linear algebra and calculus. Key themes of the 6th edition include:
The 6th edition introduced several refinements that make it a superior choice for modern students compared to older versions: Go to product viewer dialog for this item. Applied Multivariate Statistical Analysis
Matrix Algebra, Sample Geometry, and the Multivariate Normal Distribution.
by Richard A. Johnson and Dean W. Wichern remains a cornerstone textbook for experimental scientists, graduate students, and data practitioners seeking a rigorous yet accessible introduction to managing complex datasets. Matrix Algebra, Sample Geometry, and the Multivariate Normal
Inferences about Mean Vectors, Comparisons of Several Means (MANOVA), and Multivariate Linear Regression. The 6th edition is organized into four main
Features numerous real-world data sets and exercises, often including snapshots of corresponding SAS output to bridge theory and practice. Comparisons of Several Means (MANOVA)
The 6th edition is organized into four main parts, covering everything from fundamental matrix algebra to advanced grouping techniques. Key Chapters & Concepts I. Getting Started
The primary goal of this market-leading text is to impart the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. It is designed for students who have completed at least two prior statistics courses and assumes a basic comfort level with linear algebra and calculus. Key themes of the 6th edition include:
The 6th edition introduced several refinements that make it a superior choice for modern students compared to older versions: Go to product viewer dialog for this item. Applied Multivariate Statistical Analysis
