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The coefficient of relationship is a measure of the degree of consanguinity (or biological relationship) between two individuals. The term coefficient of relationship was defined by Sewall Wright in 1922, and was derived from his definition of the coefficient of inbreeding of 1921. The measure is most commonly used in genetics and genealogy.
The correlation coefficient is +1 in the case of a perfect direct (increasing) linear relationship (correlation), −1 in the case of a perfect inverse (decreasing) linear relationship (anti-correlation), [5] and some value in the open interval (,) in all other cases, indicating the degree of linear dependence between the variables. As it ...
Coefficient of Relationship and Coefficient of Inbreeding, while related (no pun intended ;-) are not the same things. The Coefficient of Relationship (R) can be stated much more simply than it is here; the equation shown uses the Coefficient of Inbreeding (F) as a required variable, but never adequately defines how it is obtained.
A constant coefficient, also known as constant term or simply constant, is a quantity either implicitly attached to the zeroth power of a variable or not attached to other variables in an expression; for example, the constant coefficients of the expressions above are the number 3 and the parameter c, involved in 3=c ⋅ x 0.
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A correlation coefficient is a numerical measure of some type of linear correlation, meaning a statistical relationship between two variables. [ a ] The variables may be two columns of a given data set of observations, often called a sample , or two components of a multivariate random variable with a known distribution .
Therefore the coefficient of inbreeding of individual G is = (+) = + = %. If the parents of an individual are not inbred themselves, the coefficient of inbreeding of the individual is one-half the coefficient of relationship between the parents. This can be verified in the previous example, as 12.5% is one-half of 25%, the coefficient of ...
A rank correlation coefficient measures the degree of similarity between two rankings, and can be used to assess the significance of the relation between them. For example, two common nonparametric methods of significance that use rank correlation are the Mann–Whitney U test and the Wilcoxon signed-rank test .