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# Correlation Coefficient (Kendall's Tau) (G Dataflow)

Version:

Computes the Kendall's Tau 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.

## Understanding the Kendall's Tau Correlation Coefficient

The Kendall's Tau correlation coefficient is a non-parametric measure of association between two data sets.

In a population with the Kendall's Tau correlation coefficient r, the odds ratio Pc /Pd of the concordant to discordant sets of observations equals (1+r)/(1-r). For example, in a population with a correlation coefficient r of 1/2, x and y are three times as likely to be concordant than discordant.

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported