Correlation Parametric and Nonparametric Measures

ISBN-10: 0761922288

ISBN-13: 9780761922285

Edition: 2002

List price: $22.00
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Description:

The authors equip the reader on how to compare and distinguish the concepts of similarity and relationship, identify the distinction between correlation and causation and to interpret correlations correctly.
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Book details

List price: $22.00
Copyright year: 2002
Publisher: SAGE Publications, Incorporated
Publication date: 6/12/2002
Binding: Paperback
Pages: 104
Size: 5.75" wide x 8.75" long x 0.25" tall
Weight: 0.242
Language: English

The goals of my research programs are to improve the quality of individual well-being, and to build a healthy workplace and society that enhance the safety and health of workers and their families. A healthy workplace or a healthy society is one in which all constituents are able to exercise their talents and gifts to achieve high performance as well as maintain psychological and physical well-being. In order to understand how to effectively build a healthy society and a healthy organization, I have taken an interdisciplinary approach over years to explore the ways of maximizing organizational as well as societal productivity, and optimizing individual potentials to pursue healthier, more secure, and safer lives. My past field and military experience have convinced me that there will be much more efficient options available if one is open to different approaches and ideas, and utilize their strengths to solve problems.

Introduction
Characteristics of a Relationship
Correlation and Causation
Correlation and Causation
Correlation and Correlational Methods
Choice of Correlation Indexes
The Pearson Product-Moment Correlation
Interpretation of Pearson r
Assumptions of Pearson r in Inferential Statistics
Sampling Distributions of the Pearson r
Properties of the Sampling Distribution of the Pearson
Null Hypothesis Tests of r = 0
Null Hypothesis Tests of r = r�
Confidence Intervals of r
Null Hypothesis Test of r1 = r2
Null Hypothesis Test for the Difference Among More Than Two Independent r's
Null Hypothesis Test for the Difference Between Two Dependent Correlations
Special Cases of The Pearson r
Point-Biserial Correlation, rpb
Phi Coefficient, f
Spearman Rank-Order Correlation, rrank
True vs. Artificially Converted Scores
Biserial Coefficient,
Tetrachoric Coefficient,
Eta Coefficient,
Other Special Cases of the Pearson r
Applications of the Pearson r
Effect Size
Power Analysis
Meta-Analysis
Utility Analysis
Reliability Estimates
Validation
Factors Affecting the Size and Interpretation of the Pearson r
Shapes of Distributions
Sample Size
Outliers
Restriction of Range
Nonlinearity
Aggregate Samples
Ecological Inference
Measurement Error
Third Variables
Other Useful Nonparametric Correlations
C and Cram�r's V Coefficients
Kendall's t Coefficient
Kendall's tb and Stuart's tc Coefficients
Goodman-Kruskal's g Coefficient
Kendall's Partial Rank-Order Correlation,
References
Lists of Tables
Lists of Figures
List of Appendixes
About the Authors
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