# Correlation Coefficient (Linear) (G Dataflow)

Version:

Computes the linear correlation coefficient between two sequences.

## x

The first input sequence.

## y

The second input sequence.

## error in

Error conditions that occur before this node runs. The node responds to this input according to standard error behavior.

Default: No error

## correlation coefficient r

Correlation coefficient between the two input sequences.

Understanding the Values of This Output

correlation coefficient r always is in the interval [-1, 1]. The following table explains the meaning of different correlation coefficient r values:

correlation coefficient r Explanation
1

x and y have a complete positive correlation. The data points from x and y lie on a perfectly straight, positively-sloped line.

-1

x and y have a complete negative correlation. The data points from x and y lie on a perfectly straight, negatively-sloped line.

0

x and y have no correlation.

## r^2

Square of the correlation coefficient.

## error out

Error information. The node produces this output according to standard error behavior.

## Algorithm for Computing the Linear Correlation Coefficient

The linear correlation coefficient also is known as the product-moment coefficient of correlation or Pearson's correlation. The following equation describes the linear correlation coefficient:

$r=\frac{\mathrm{\Sigma }{z}_{x}{z}_{y}}{n}$

where zx and zy are the standardized z-values of x and y. The standardized z-values indicate how many standard deviations x and y are above or below the mean.

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported