Correlation Coefficient
Dataset X :

Dataset Y :

Correlation Coefficient :

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# Correlation Coefficient {corr(X,Y)} Calculator

getcalc.com's Correlation Coefficient calculator, formula & work with steps to find the degree or magnitude of linear relationship between two or more variables in statistical experiments. Supply the values and check if two data sets or variables are positively or negatively correlated. This calculator is featured to generate the complete work with steps for any corresponding input values of correlation coefficient.

Input Parameters
Users may supply the values for the below input parameters to find if X & Y variables are positively or negatively correlated by using this calculator.

Random Variable X :
The collection random variables for X that must be number, date, time or duration. All values must be same in kind.

Random Variable Y :
The collection random variables for Y that must be number, date, time or duration. All values must be same in kind.

## What is Correlation Coefficient?

Correlation Coefficient is a method used in the context of probability & statistics often denoted by {Corr(X, Y)} or r(X, Y) used to find the degree or magnitude of linear relationship between two or more variables in statistical experiments. It is a ratio of covariance of random variables X and Y to the product of standard deviation of random variable X and standard deviation of random variable Y. Generally, correlation refers to the change in one variable effects the change in another variable and it is classified into three types as positive correlation, negative correlation and zero correlation.

It always lie between -1 and +1 which represented by -1 ≤ r(X, Y) ≤ 1.
if r(X, Y) = 1 then the variables X and Y are positively correlated.
if r(X, Y) = -1 then the variables X and Y are negatively correlated.
if r(X, Y) = 0 then there is no correlation between the variables X and Y.

Income & expenditure, shares & debentures, rainfall & yield, supply & demand, demand & price blood pressure & age, age & income, expenditure &age, family & number of persons, age & height, age & weight are some of the examples for correlation. It's a measure of degree of relationship between two or more variables. It's also stated that it is an analysis between covariance between two or more variables. The range of correlation is between -1 to +1. There are different types of correlation measured in statistics based on the random variables & outcome of such calculations. Positive or negative, linear or non-linear, partial or total and simple or multiple correlation are the different types of correlation.

Formulas
The below formula is the mathematical representation for correlation r. Users may refer this below formula to know what are all the input parameters are being used to find the correlation between two or more variables. 