Correlation coefficient

Correlation coefficient and Covariance
One problem with covariance is that it is sensitive to the scales on which the values of the r.v. are measured. Say you're computing the covariance between "Height" and "Weight" in a population.

Correlation Coefficient
Correlation coefficient is standardized angular separation by centering the coordinates to its mean value. The value is between -1 and +1. It measures similarity rather than distance or dissimilarity.

The Matthews correlation coefficient is used in machine learning as a measure of the quality of binary (two-class) classifications.

Probability Plot Correlation Coefficient Plot
Purpose:
Graphical Technique for Finding the Shape Parameter of a Distributional Family that Best Fits a Data Set ...

Are correlation coefficients "additive?" No, they are not. For example, an average of correlation coefficients in a number of samples does not represent an "average correlation" in all those samples.

Pearson Squared: Use the squared Pearson Correlation coefficient to cluster together genes with similar or opposite behaviors (i.e. genes that are highly correlated and those that are highly anti-correlated are clustered together).

Some redundancies can be detected by correlation analysis correlation coefficient ,The χ2 value (also known as the Pearson χ2 statistic) is computed as: ...

that the learning result is an average weighted by an exponentiallyâ€'decaying time factor: Let Zn be ±1 according to whether the n-th event is rewarded or extinguished and replace pn by cn-2pn-1 so that -1

See also: Distribution, Normal distribution, Variance, Standard Deviation, Regression