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Inequality (mathematics)

In mathematics, an inequality is a relation which makes a non-equal comparison between two numbers or other mathematical expressions. It is used most often to compare two numbers on the number line by their size. The main types of inequality are less than and greater than.

Notation
There are several different notations used to represent different kinds of inequalities: • The notation a b means that a is greater than b. In either case, a is not equal to b. These relations are known as strict inequalities, For example, In 1670, John Wallis used a single horizontal bar above rather than below the . Later in 1734, ≦ and ≧, known as "less than (greater-than) over equal to" or "less than (greater than) or equal to with double horizontal bars", first appeared in Pierre Bouguer's work . After that, mathematicians simplified Bouguer's symbol to "less than (greater than) or equal to with one horizontal bar" (≤), or "less than (greater than) or slanted equal to" (⩽). The relation not greater than can also be represented by a \ngtr b, the symbol for "greater than" bisected by a slash, "not". The same is true for not less than, a \nless b. The notation ab means that a is not equal to b; this inequation sometimes is considered a form of strict inequality. It does not say that one is greater than the other; it does not even require a and b to be a member of an ordered set. In engineering sciences, less formal use of the notation is to state that one quantity is "much greater" than another, normally by several orders of magnitude. • The notation ab means that a is much less than b. • The notation ab means that a is much greater than b. This implies that the lesser value can be neglected with little effect on the accuracy of an approximation (such as the case of ultrarelativistic limit in physics). In all of the cases above, any two symbols mirroring each other are symmetrical; a a are equivalent, etc. == Properties on the number line ==
Properties on the number line
Inequalities are governed by the following properties. All of these properties also hold if all of the non-strict inequalities (≤ and ≥) are replaced by their corresponding strict inequalities () and — in the case of applying a function — monotonic functions are limited to strictly monotonic functions. Converse The relations ≤ and ≥ are each other's converse, meaning that for any real numbers a and b: Transitivity The transitive property of inequality states that for any real numbers a, b, c: If either of the premises is a strict inequality, then the conclusion is a strict inequality: Addition and subtraction on both sides of an inequality, when a and b are positive real numbers: (this is true because the natural logarithm is a strictly increasing function.) == Formal definitions and generalizations ==
Formal definitions and generalizations
A (non-strict) partial order is a binary relation ≤ over a set P which is reflexive, antisymmetric, and transitive. That is, for all a, b, and c in P, it must satisfy the three following clauses: • aa (reflexivity) • if ab and ba, then a = b (antisymmetry) • if ab and bc, then ac (transitivity) A set with a partial order is called a partially ordered set. Those are the very basic axioms that every kind of order has to satisfy. A strict partial order is a relation < that satisfies • aa (irreflexivity), • if a < b, then ba (asymmetry), • if a < b and b < c, then a < c (transitivity), where means that does not hold. Some types of partial orders are specified by adding further axioms, such as: • Total order: For every a and b in P, ab or ba . • Dense order: For all a and b in P for which a < b, there is a c in P such that a < c < b. • Least-upper-bound property: Every non-empty subset of P with an upper bound has a least upper bound (supremum) in P. Ordered fields If (F, +, ×) is a field and ≤ is a total order on F, then (F, +, ×, ≤) is called an ordered field if and only if: • ab implies a + cb + c; • 0 ≤ a and 0 ≤ b implies 0 ≤ a × b. Both and are ordered fields, but cannot be defined in order to make an ordered field, because −1 is the square of i and would therefore be positive. Besides being an ordered field, R also has the Least-upper-bound property. In fact, R can be defined as the only ordered field with that quality. == Chained notation ==
Chained notation
The notation '''a 1 ≤ a2 ≤ ... ≤ ''a'n means that a''iai+1 for i = 1, 2, ..., n − 1. By transitivity, this condition is equivalent to aiaj for any 1 ≤ ijn. When solving inequalities using chained notation, it is possible and sometimes necessary to evaluate the terms independently. For instance, to solve the inequality 4x 1 2 > a3 4 > a5 6 > ... . Mixed chained notation is used more often with compatible relations, like <, =, ≤. For instance, a < b = cd means that a < b, b = c, and cd. This notation exists in a few programming languages such as Python. In contrast, in programming languages that provide an ordering on the type of comparison results, such as C, even homogeneous chains may have a completely different meaning. ==Sharp inequalities==
Sharp inequalities
An inequality is said to be sharp if it cannot be relaxed and still be valid in general. Formally, a universally quantified inequality φ is called sharp if, for every valid universally quantified inequality ψ, if holds, then also holds. For instance, the inequality is sharp, whereas the inequality is not sharp. ==Inequalities between means==
Inequalities between means
There are many inequalities between means. For example, for any positive numbers a1, a2, ..., an we have : H\le G\le A\le Q, where they represent the following means of the sequence: • Harmonic mean : H = \frac{n}{\frac{1}{a_1} + \frac{1}{a_2} + \cdots + \frac{1}{a_n}} • Geometric mean : G = \sqrt[n]{a_1 \cdot a_2 \cdots a_n} • Arithmetic mean : A = \frac{a_1 + a_2 + \cdots + a_n}{n} • Quadratic mean : Q = \sqrt{\frac{a_1^2 + a_2^2 + \cdots + a_n^2}{n}} ==Cauchy–Schwarz inequality==
Cauchy–Schwarz inequality
The Cauchy–Schwarz inequality states that for all vectors u and v of an inner product space it is true that |\langle \mathbf{u},\mathbf{v}\rangle| ^2 \leq \langle \mathbf{u},\mathbf{u}\rangle \cdot \langle \mathbf{v},\mathbf{v}\rangle, where \langle\cdot,\cdot\rangle is the inner product. Examples of inner products include the real and complex dot product; In Euclidean space Rn with the standard inner product, the Cauchy–Schwarz inequality is \biggl(\sum_{i=1}^n u_i v_i\biggr)^2\leq \biggl(\sum_{i=1}^n u_i^2\biggr) \biggl(\sum_{i=1}^n v_i^2\biggr). ==Power inequalities==
Power inequalities
A power inequality is an inequality containing terms of the form ab, where a and b are real positive numbers or variable expressions. They often appear in mathematical olympiads exercises. Examples: • For any real x, e^x \ge 1+x. • If x > 0 and p > 0, then \frac1p\left(x^p - 1\right) \ge \ln(x) \ge \frac1p\left(1 - \frac{1}{x^p}\right). In the limit of p → 0, the upper and lower bounds converge to ln(x). • If x > 0, then x^x \ge \left( \frac{1}{e}\right)^\frac{1}{e}. • If x > 0, then x^{x^x} \ge x. • If x, y, z > 0, then \left(x+y\right)^z + \left(x+z\right)^y + \left(y+z\right)^x > 2. • For any real distinct numbers a and b, \frac{e^b-e^a}{b-a} > e^\frac{a+b}{2}. • If x, y > 0 and 0 x^p+y^p > \left(x+y\right)^p. • If x, y, z > 0, then x^x y^y z^z \ge \left(xyz\right)^\frac{x+y+z}{3}. • If a, b > 0, then a^a + b^b \ge a^b + b^a. • If a, b > 0, then a^{ea} + b^{eb} \ge a^{eb} + b^{ea}. • If a, b, c > 0, then a^{2a} + b^{2b} + c^{2c} \ge a^{2b} + b^{2c} + c^{2a}. • If a, b > 0, then a^b + b^a > 1. == Well-known inequalities ==
Well-known inequalities
Complex numbers and inequalities
The set of complex numbers \mathbb{C} with its operations of addition and multiplication is a field, but it is impossible to define any relation so that (\Complex, +, \times, \leq) becomes an ordered field. To make (\mathbb{C}, +, \times, \leq) an ordered field, it would have to satisfy the following two properties: • if , then ; • if and , then . Because ≤ is a total order, for any number a, either or (in which case the first property above implies that ). In either case ; this means that and ; so and , which means (−1 + 1) > 0; contradiction. However, an operation ≤ can be defined so as to satisfy only the first property (namely, "if , then "). Sometimes the lexicographical order definition is used: • , if • , or • and It can easily be proven that for this definition implies . == Systems of inequalities ==
Systems of inequalities
Systems of linear inequalities can be simplified by Fourier–Motzkin elimination. The cylindrical algebraic decomposition is an algorithm that allows testing whether a system of polynomial equations and inequalities has solutions, and, if solutions exist, describing them. The complexity of this algorithm is doubly exponential in the number of variables. It is an active research domain to design algorithms that are more efficient in specific cases. ==See also==
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