What is the formula for Pearson correlation?

The Pearson correlation is denoted with r and calculated as follows:

\[r = \frac{covariance\:of\:x\:and\:y}{variability\:of\:x\:and\:y\:seperately}\]

or:

\[r = \frac{\sum{(x-\bar{x})(y-\bar{y})}}{\sqrt{\sum{(x-\bar{x})^2}\sum{(y-\bar{y})^2}}}\]

which is the same as:

\[r = \frac{N \sum{xy}-(\sum{x})(\sum{y})}{\sqrt{[N\sum{x^2}-(\sum{x})^2] [N\sum{y^2}-(\sum{y})^2]}}\]

  • N: number of pairs of scores
  • x: x scores
  • y: y scores
  • : mean of x scores
  • ȳ: mean of y scores

 

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Applying correlation, regression and linear regression

Applying correlation, regression and linear regression

Correlation, Regression, Linear Regression Correlation versus regression Correlation Regression Back to top Correlation versus regression Correlation and Regression are the two analysis based on multivariate distribution. A multivariate distribution is described as a distribution of multiple variables. Correlation is described as the analysis which lets us know the association or the absence of the relationship between two variables ‘x’ and....... read more
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26-02-2019

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