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A statistic representing how closely two variables co-vary; it can vary from -1 (perfect negative correlation) through 0 (no correlation) to +1 (perfect positive correlation)
The number which expresses this relation is called the coefficientofcorrelation.
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The formula for finding the coefficientofcorrelation can be understood from examples of its application.
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Suppose, for example, that in correlating crime and unemployment, the coefficientofcorrelation were found to be .47.
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The linear coefficientofcorrelation between mean MND and mean nuclear area was 0.84.
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If there is no relationship indicated by the measures of achievements which we have found, then the coefficientofcorrelation becomes 0.
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The coefficientofcorrelation between number of abnormal nerves and the value of PNI-R mounted up to -0.87.
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If crime were never found in unemployment, and unemployment never in crime, the coefficientofcorrelation would be -1, indicating a perfect inverse relationship.
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Results: The median Pearson coefficientofcorrelation between manually and automatically withdrawn blood samples was 0.976 (0.953-0.996).
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If in every case of unemployment crime were found and in every case of crime, unemployment, the coefficientofcorrelation would be +1.
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The coefficientofcorrelation between tumor volume and serum alpha-fetoprotein of tumor-bearing mice was 0.51 in YST-1 and 0.42 in YST-2.
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Descriptive statistics, coefficientsofcorrelation and of variation (CV) were performed.
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Convergent validity was determined using Pearson coefficientsofcorrelation.
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The analyses consisted, first, in establishing the matrix of correlations between these self-reports total scores, using Pearson's coefficientsofcorrelation.