## 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.

## 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 *z*_{x} and *z*_{y} 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