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Correlation: Parametric and Nonparametric Measures

Correlation: Parametric and Nonparametric Measures

Peter Y. Chen, Paula M. Popovich
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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.
Categories:
Volume:
139
Year:
2002
Edition:
1
Publisher:
Sage Publications, Inc
Language:
english
Pages:
105
ISBN 10:
0761922288
ISBN 13:
9780761922285
Series:
Quantitative Applications in the Social Sciences
File:
PDF, 4.77 MB
IPFS:
CID , CID Blake2b
english, 2002
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