Understanding Correlation Matrices

Correlation matrices and covariance matrices are essential statistical tools that provide insights into the relationships between variables. This volume discusses their features, applications, and graphical approaches, with examples ranging from intelligence to health and sports. It is useful for undergraduate and graduate statistics classrooms and research laboratories.

Format: Paperback / softback
Length: 136 pages
Publication date: 02 March 2021
Publisher: SAGE Publications Inc

Correlation matrices, along with their unstandardized counterparts, covariance matrices, play a fundamental role in the majority of statistical methods employed by researchers today. These matrices are far more than mere collections of correlation coefficients; they hold significant multivariate implications. The value of one correlation in the matrix imposes constraints on the values of the others, and this concept forms a central theme throughout the volume. Alexandria Hadd and Joseph Lee Rodgers, in their comprehensive work, delve into various aspects of correlation matrices. They discuss statistical hypothesis tests, their significance in factor analysis and structural equation modeling, and graphical approaches. Through a wide range of lively examples, Hadd and Rodgers illustrate the discussions, encompassing correlations between intelligence measured at different ages throughout adolescence, correlations between country characteristics such as public health expenditures, health life expectancy, and adult mortality, correlations between well-being and state-level vital statistics, correlations between the racial composition of cities and professional sports teams, and correlations between childbearing intentions and childbearing outcomes across the reproductive life course. This volume serves as a valuable resource for students and practitioners across a diverse range of disciplines, including undergraduate and graduate statistics classrooms, as well as research laboratories. Its comprehensive coverage and insightful examples make it an essential tool for understanding and applying correlation analysis in statistical research and practice.

Weight: 174g
Dimension: 141 x 219 x 11 (mm)
ISBN-13: 9781544341095