A **correlation coefficient** is a numerical measure of some type of correlation, meaning a statistical relationship between two variables. ^{}The variables may be two columns of a given data set of observations, often called a sample, or two components of a multivariate random variable with a known distribution.

Several types of correlation coefficient exist, each with their own definition and own range of usability and characteristics. They all assume values in the range from −1 to +1, where ±1 indicates the strongest possible agreement and 0 the strongest possible disagreement.^{} As tools of analysis, correlation coefficients present certain problems, including the propensity of some types to be distorted by outliers and the possibility of incorrectly being used to infer a causal relationship between the variables (for more, see Correlation does not imply causation).

A complimentary description for this term is that it is a statistic used for quantifying the strength of a linear association between variable inputs and outputs. It ranges from +1 (perfect positive correlation: higher input goes with higher output) to -1 (perfect negative correlation: higher input goes with lower output).

#### References

Wikipedia. Correlation Coefficient. https://en.wikipedia.org/wiki/Correlation_coefficient