# Spearman's Rank Correlation Coefficient (RHO) Calculator

An online Spearman's rank correlation coefficient (RHO) calculator to calculate the R-value and the conclusion termed as the Spearman's RHO. The rank correlation coefficient, also termed as Spearman's RHO is a nonparametric measure of statistical dependence between two variables.

## Spearman's RHO Calculation

An online Spearman's rank correlation coefficient (RHO) calculator to calculate the R-value and the conclusion termed as the Spearman's RHO. The rank correlation coefficient, also termed as Spearman's RHO is a nonparametric measure of statistical dependence between two variables.

Code to add this calci to your website

#### Formula:

R = 1 - ( (6× σd^{2}) / (n^{3} - n) )
**Where,**
σ = Sumation of differences
d = Differences
n = Number of Datas
R = Rank Value
This online **Spearman's rank correlation coefficient (RHO) calculator** helps you to do Spearman's RHO calculation with ease. The correlation coefficient helps you in assessing the relationship between two variables in a monotonic function. The Sperman's correlation, named after Charles Sperman, between two variables is equal to the Pearson correlation between the rank values of those two variables. The correlation between two variables will be high when observations have a similar rank between the two variables and low when observations have a dissimilar rank between the two variables. Enter the number of sets and enter the values for the sets in this RHO calculator to know the ranks for the sets and the R value and conclusion whether it is a correlation value or not.

#### Example

** Let Set A 4 , 8 , 9 , 11 , 3 Set B 7 , 2 , 6 , 3 , 14 find Spearman's Rank Correlation**

Set A | Set B |

4 | 7 |

8 | 2 |

9 | 6 |

11 | 3 |

3 | 14 |

Set A | Rank A | Set B | Rank B | d | d² |

4 | 4 | 7 | 2 | 2 | 4 |

8 | 3 | 2 | 5 | 2 | 4 |

9 | 2 | 6 | 3 | 1 | 1 |

11 | 1 | 3 | 4 | 3 | 9 |

3 | 5 | 14 | 1 | 4 | 16 |

5 |

R = 1 - ( (6× σd^{2}) / (n^{3} - n) )

=1 - ( (6× 34) / (5^{3} - 5) )

=1 - ( (204) / (120) )

R = - 0.7

From the below table , It is a strong negative correlation value

R Value | Correlation Conclusion |

-1 | Perfect negative |

between -1 and -0.5 | Strong negative |

between -0.5 and 0 | Weak negative |

0 | No correlation |

between 0 and 0.5 | Weak positive |

between 0.5 and 1 | Strong positive |

1 | Perfect positive |