(noun) In statistical analysis, a standardized measure of the covariance between two variables expressed between -1 and +1. The sign of the coefficient indicates the direction of the relationship while the magnitude is indicated by the value of the coefficient with 0 indicating absolutely no correlation and a value of ±1 indicating perfect correlation.
Example: The correlation coefficient of -.85 indicates a strong negative correlation between two variables.
Audio Pronunciation: (cor·re·la·tion co·ef·fi·cient)
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- Plural: correlation coefficients
- The most common test for correlation is the Pearson product-movement correlation (commonly referred to as Pearson correlation) which tests the linear correlation between two variables where data approximates interval level characteristics.
- Pearson correlation produces a correlation coefficient, Pearson’s r, which is an absolute measure of the strength of association between two variables as they approximate a linear relationship. The value of the coefficient can range from -1 to +1. When r = 0; the two variables have no linear relationship. While the size and sign of the coefficient are important, the coefficient must also be statistically significant for a relationship between two variables to be considered present in the data.
- Correlation forms the basis of regression analysis. Regression allows for the effects of additional variables to be considered in the relationship of x on y.
- Also called:
- coefficient of association
- coefficient of correlation
- coefficient of association
- Correlation coefficient used in a sentence: The negative correlation coefficient is also significant, indicating that scores on one variable are inversely associated with scores on the second variable.
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