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Correlation
Parametric and Nonparametric Measures
First Edition
- Peter Y Chen - Auburn University, USA, Colorado State University, USA
- Paula M Popovich - Ohio University, USA
Volume:
139
June 2002 | 104 pages | SAGE Publications, Inc
Correlations, in general, and the Pearson product-moment correlation in particular, can be used for many research purposes, ranging from describing a relationship between two variables as a descriptive statistic to examining a relationship between two variables in a population as an inferential statistic, or to gauge the strength of an effect, or to conduct a meta-analytic study. How can correlation be more effectively used so that one doesn't misinterpret the data? This book reveals how to do this by examining Pearson r from its conceptual meaning, to assumptions, special cases of the Pearson r, the biserial coefficient and tetrachoric coefficient estimates of the Pearson r, its uses in research (including effect size, power analysis, meta-analysis, utility analysis, reliability estimates and validation), factors that affect the Pearson r, and finally to additional nonparametric correlation indexes. After reading this book, the reader will be able to compare and distinguish the concepts of similarity and relationship, identify the distinction between correlation and causation, and to interpret correlations correctly.
Ch 1. Introduction
Ch 2. The Pearson Product-Moment Correlation
Chapter 3: Special Cases of The Pearson r
Chapter 4: Applications of the Pearson r
Chapter 5: Factors Affecting the Size and Interpretation of the Pearson r
Chapter 6: Other Useful Nonparametric Correlations
References
Lists of Tables
Lists of Figures
List of Appendixes
About the Authors
I need to see more examples... I understand the book needs to be brief...
School Of Management, Walden University
April 17, 2013
