### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.9 Reference Guide (DRAFT) »
- Statistical functions (`scipy.stats`) »
- Statistical functions for masked arrays (`scipy.stats.mstats`) »

# scipy.stats.mstats.kendalltau

`scipy.stats.mstats.``kendalltau`(x, y, use_ties=True, use_missing=False)

  Computes Kendall’s rank correlation tau on two variables x and y.

  Parameters : | xdata: sequence : First data list (for example, time). ydata: sequence : Second data list. use_ties: {True, False} optional : Whether ties correction should be performed. use_missing: {False, True} optional : Whether missing data should be allocated a rank of 0 (False) or the average rank (True)
  Returns : | tau : float Kendall tau prob : float Approximate 2-side p-value.

### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.9 Reference Guide (DRAFT) »
- Statistical functions (`scipy.stats`) »
- Statistical functions for masked arrays (`scipy.stats.mstats`) »