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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.
Coefficient of relationship – Mathematical guess about inbreeding; Cognatic kinship – Mode of descent; Cousin marriage in the Middle East – Consanguineous relationships in the Middle East; Endogamy – Marrying within a specific ethnic group, class, or social group; Exogamy – Social arrangement which only allows marriage outside a ...
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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.
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 relationship between an uncle and a niece.
Malecot's coancestry coefficient, , refers to an indirect measure of genetic similarity of two individuals which was initially devised by the French mathematician Gustave Malécot. f {\displaystyle f} is defined as the probability that any two alleles , sampled at random (one from each individual), are identical copies of an ancestral allele.
Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).