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Rank correlation from following data Judge x : 52, 53, 42, 60, 45, 41, 37, 38, 25, 27 Judge y: 65,68,43,38,77,48,35,30,25,50
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Rank correlation from following data Judge x : 52, 53, 42, 60, 45, 41,...
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Rank correlation from following data Judge x : 52, 53, 42, 60, 45, 41,...
To calculate the rank correlation between Judge x and Judge y, we need to assign ranks to the scores for each judge and then calculate the correlation between the ranks. The ranks are as follows:

Judge x: 8, 7, 10, 2, 9, 11, 12, 11, 1, 3
Judge y: 2, 1, 9, 11, 4, 8, 12, 13, 14, 6

To calculate the rank correlation, we can use the Spearman's rank correlation coefficient formula:

rs = 1 - (6Σd^2)/(n(n^2-1))

where:
d = difference in ranks between the two judges for each score
n = number of scores

Using this formula, we can calculate the rank correlation as follows:

Σd^2 = (8-2)^2 + (7-1)^2 + (10-9)^2 + (2-11)^2 + (9-4)^2 + (11-8)^2 + (12-14)^2 + (11-13)^2 + (1-12)^2 + (3-6)^2
Σd^2 = 304

n = 10

rs = 1 - (6Σd^2)/(n(n^2-1))
rs = 1 - (6(304))/(10(10^2-1))
rs = 1 - (6(304))/(990)
rs = 1 - 1.83
rs = -0.83

Therefore, the rank correlation between Judge x and Judge y is -0.83. This indicates a strong negative correlation between the two judges' scores.
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Rank correlation from following data Judge x : 52, 53, 42, 60, 45, 41, 37, 38, 25, 27 Judge y: 65,68,43,38,77,48,35,30,25,50 Related: Rank Correlation - Correlation & Regression, Business Mathematics & Statistics
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