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In mathematics, a codomain or set of destination of a function is a set into which all of the output of the function is constrained to fall. It is the set Y in the notation f: X → Y. The term range is sometimes ambiguously used to refer to either the codomain or the image of a function. A codomain is part of a function f if f is defined as a ...
A predicate is a statement or mathematical assertion that contains variables, sometimes referred to as predicate variables, and may be true or false depending on those variables’ value or values. In propositional logic, atomic formulas are sometimes regarded as zero-place predicates. [1] In a sense, these are nullary (i.e. 0- arity) predicates.
where E is the expected value operator. Notably, correlation is dimensionless while covariance is in units obtained by multiplying the units of the two variables. If Y always takes on the same values as X, we have the covariance of a variable with itself (i.e. ), which is called the variance and is more commonly denoted as the square of the ...
For a set of random variables X n and corresponding set of constants a n (both indexed by n, which need not be discrete), the notation = means that the set of values X n /a n converges to zero in probability as n approaches an appropriate limit. Equivalently, X n = o p (a n) can be written as X n /a n = o p (1), i.e.
Affine combination. In mathematics, an affine combination of x1, ..., xn is a linear combination. such that. Here, x1, ..., xn can be elements (vectors) of a vector space over a field K, and the coefficients are elements of K. The elements x1, ..., xn can also be points of a Euclidean space, and, more generally, of an affine space over a field K.
In mathematics, in particular field theory, the conjugate elements or algebraic conjugates of an algebraic element α, over a field extension L/K, are the roots of the minimal polynomial pK,α(x) of α over K. Conjugate elements are commonly called conjugates in contexts where this is not ambiguous. Normally α itself is included in the set of ...
Lebesgue's density theorem asserts that for almost every point x of A the density. exists and is equal to 0 or 1. In other words, for every measurable set A, the density of A is 0 or 1 almost everywhere in Rn. [1] However, if μ (A) > 0 and μ (Rn \ A) > 0, then there are always points of Rn where the density is neither 0 nor 1.
The value of a mathematical expression is the object assigned to this expression when the variables and constants in it are assigned values. The value of a function, given the value (s) assigned to its argument (s), is the quantity assumed by the function for these argument values. [1][2] For example, if the function f is defined by f(x) = 2x2 ...