Correlation

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.

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• Ch 1. IntroductionCharacteristics of a RelationshipCorrelation and CausationCorrelation and CausationCorrelation and Correlational MethodsChoice of Correlation IndexesCh 2. The Pearson Product-Moment CorrelationInterpretation of Pearson rAssumptions of Pearson r in Inferential StatisticsSampling Distributions of the Pearson r Properties of the Sampling Distribution of the Pearson Null Hypothesis Tests of r = 0Null Hypothesis Tests of r = røConfidence Intervals of rNull Hypothesis Test of r1 = r2Null Hypothesis Test for the Difference Among More Than Two Independent r′sNull Hypothesis Test for the Difference Between Two Dependent CorrelationsChapter 3: Special Cases of The Pearson rPoint-Biserial Correlation, rpbPhi Coefficient, fSpearman Rank-Order Correlation, rrankTrue vs. Artificially Converted ScoresBiserial Coefficient, Tetrachoric Coefficient, Eta Coefficient, Other Special Cases of the Pearson rChapter 4: Applications of the Pearson rApplication I: Effect SizeApplication II: Power AnalysisApplication III: Meta-AnalysisApplication IV: Utility AnalysisApplication V: Reliability EstimatesApplication VI: ValidationChapter 5: Factors Affecting the Size and Interpretation of the Pearson rShapes of DistributionsSample Size OutliersRestriction of RangeNonlinearityAggregate SamplesEcological InferenceMeasurement ErrorThird VariablesChapter 6: Other Useful Nonparametric CorrelationsC and Cramér′s V CoefficientsKendall′s t CoefficientKendall′s tb and Stuart′s tc CoefficientsGoodman-Kruskal′s g CoefficientKendall′s Partial Rank-Order Correlation, ReferencesLists of TablesLists of FiguresList of AppendixesAbout the Authors