As a simple example, one would expect the age and height of a sample of teenagers from a high school to have a Pearson correlation coefficient significantly greater than 0, but less than 1 (as 1 would represent an unrealistically perfect correlation).Įxamples of scatter diagrams with different values of correlation coefficient ( ρ) Several sets of ( x, y) points, with the correlation coefficient of x and y for each set. As with covariance itself, the measure can only reflect a linear correlation of variables, and ignores many other types of relationships or correlations. It is the ratio between the covariance of two variables and the product of their standard deviations thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1. In statistics, the Pearson correlation coefficient ( PCC, pronounced / ˈ p ɪər s ən/) ― also known as Pearson's r, the Pearson product-moment correlation coefficient ( PPMCC), the bivariate correlation, or colloquially simply as the correlation coefficient ― is a measure of linear correlation between two sets of data. For broader coverage of this topic, see Correlation coefficient.
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