Pearson correlation coefficient
From Cohen Courses
Jump to navigationJump to searchThis is a method discussed in Social Media Analysis 10-802 in Spring 2010.
Its a metric to measure dependence between two random variables. It is defined as follows :
Corr(X,Y) = cov(X,Y) / (var(X) * var(Y)) where, * Corr(X,Y) : Pearson correlation coefficient between X and Y * cov(X,Y) : Covariance between X and Y * var(X) : variance of variable X
- The correlation coefficient ranges from −1 to 1.
- A value of 1 implies that a linear equation describes the relationship between X and Y perfectly, with all data points lying on a line for which Y increases as X increases.
- A value of −1 implies that all data points lie on a line for which Y decreases as X increases.
- A value of 0 implies that there is no linear correlation between the variables.
