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Bennett's inequality, an upper bound on the probability that the sum of independent random variables deviates from its expected value by more than any specified amount Bhatia–Davis inequality , an upper bound on the variance of any bounded probability distribution
A power inequality is an inequality containing terms of the form a b, where a and b are real positive numbers or variable expressions. They often appear in mathematical olympiads exercises. Examples:
Ladyzhenskaya's inequality; Landau–Kolmogorov inequality; Landau-Mignotte bound; Lebedev–Milin inequality; Leggett inequality; Leggett–Garg inequality; Less-than sign; Levinson's inequality; Lieb–Oxford inequality; Lieb–Thirring inequality; Littlewood's 4/3 inequality; Log sum inequality; Łojasiewicz inequality; Lubell–Yamamoto ...
In mathematics, an inequation is a statement that an inequality holds between two values. [1] [2] It is usually written in the form of a pair of expressions denoting the values in question, with a relational sign between them indicating the specific inequality relation. Some examples of inequations are: <
Two-dimensional linear inequalities are expressions in two variables of the form: + < +, where the inequalities may either be strict or not. The solution set of such an inequality can be graphically represented by a half-plane (all the points on one "side" of a fixed line) in the Euclidean plane. [2]
Many important inequalities can be proved by the rearrangement inequality, such as the arithmetic mean – geometric mean inequality, the Cauchy–Schwarz inequality, and Chebyshev's sum inequality. As a simple example, consider real numbers : By applying with := for all =, …,, it follows that + + + + + + for every permutation of , …,.
where , is the inner product.Examples of inner products include the real and complex dot product; see the examples in inner product.Every inner product gives rise to a Euclidean norm, called the canonical or induced norm, where the norm of a vector is denoted and defined by ‖ ‖:= , , where , is always a non-negative real number (even if the inner product is complex-valued).
Muirhead's inequality states that [a] ≤ [b] for all x such that x i > 0 for every i ∈ { 1, ..., n} if and only if there is some doubly stochastic matrix P for which a = Pb. Furthermore, in that case we have [ a ] = [ b ] if and only if a = b or all x i are equal.