Difference between revisions of "Kendall's Tau Test"

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Let (x1, y1), (x2, y2), …, (xn, yn) be a set of observations of the joint random variables X and Y respectively,  
 
Let (x1, y1), (x2, y2), …, (xn, yn) be a set of observations of the joint random variables X and Y respectively,  
 
such that all the values of <math>(x_i)</math> and <math>(y_i)</math> are unique.
 
such that all the values of <math>(x_i)</math> and <math>(y_i)</math> are unique.
  * concordant if <math>(x_i > x_j)</math> and <math>(y_i > y_j)}</math> or <math>(x_i < x_j)</math> and <math>(y_i < y_j)</math>.
+
  * concordant if <math>(x_i > x_j)</math> and <math>(y_i > y_j)</math> or <math>(x_i < x_j)</math> and <math>(y_i < y_j)</math>.

Revision as of 09:04, 3 May 2017

KENDALLSTAUTEST(Range1,Range2,alpha,NewTableFlag)


  • is the array of x values.
  • is the array of y values.
  • is the value from 0 to 1.
  • is either TRUE or FALSE. TRUE for getting results in a new cube. FALSE will display results in the same cube.

Description

  • It is a statistic test used to measure the ordinal association between two measured quantities.
  • It is a measure of rank correlation: the similarity of the orderings of the data when ranked by each of the quantities.
  • Kendall correlation between two variables will be high when observations have a similar rank.
  • It will be low when observations have a dissimilar rank between the two variables.

Let (x1, y1), (x2, y2), …, (xn, yn) be a set of observations of the joint random variables X and Y respectively, such that all the values of and are unique.

* concordant if  and  or  and .