In mathematics, an inequality is a relation that holds between two values when they are different (see also: equality).

The notation a ≠ b means that a is not equal to b.
 It does not say that one is greater than the other, or even that they can be compared in size.
If the values in question are elements of an ordered set, such as the or the , they can be compared in size.

The notation a < b means that a is less than b.

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. The notation a < b may also be read as " a is strictly less than b".
In contrast to strict inequalities, there are two types of inequality relations that are not strict:

The notation a ≤ b means that a is less than or equal to b (or, equivalently, not greater than b, or at most b); "not greater than" can also be represented by the symbol for "greater than" bisected by a vertical line, "not." (The unicode for ≤ is "U+ 2264".)

The notation a ≥ b means that a is greater than or equal to b (or, equivalently, not less than b, or at least b),; "not less than" can also be represented by the symbol for "less than" bisected by a vertical line, "not." (The unicode for ≥ is "U+ 2265".)
In engineering sciences, a 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 a ≪ b means that a is much less than b. (In measure theory, however, this notation is used for absolute continuity, an unrelated concept.)

The notation a ≫ b means that a is much greater than b.
Properties
Inequalities are governed by the following properties. All of these properties also hold if all of the nonstrict inequalities (≤ and ≥) are replaced by their corresponding strict inequalities (< and >) and (in the case of applying a function) monotonic
functions are limited to
strictly monotonic functions.
Transitivity
The transitive property of inequality states:

For any a, b, c:

If a ≥ b and b ≥ c, then a ≥ c.

If a ≤ b and b ≤ c, then a ≤ c.

If either of the premises is a strict inequality, then the conclusion is a strict inequality:

If a ≥ b and b > c, then a > c

If a > b and b ≥ c, then a > c

Since a = b implies a ≥ b these imply:

If a = b and b > c, then a > c

If a > b and b = c, then a > c
Converse
The relations ≤ and ≥ are each other's converse:

For any a and b:

If a ≤ b, then b ≥ a.

If a ≥ b, then b ≤ a.
Addition and subtraction
A common constant
c may be
addition to or
subtraction from both sides of an inequality:

For any a, b, c

If a ≤ b, then a + c ≤ b + c and a − c ≤ b − c.

If a ≥ b, then a + c ≥ b + c and a − c ≥ b − c.
i.e., the real numbers are an ordered group under addition.
Multiplication and division
The properties that deal with
multiplication and division state:

For any real numbers, a, b and nonzero c:

If c is positive number, then multiplying or dividing by c does not change the inequality:

If a ≥ b and c > 0, then ac ≥ bc and a/c ≥ b/c.

If a ≤ b and c > 0, then ac ≤ bc and a/c ≤ b/c.

If c is negative number, then multiplying or dividing by c inverts the inequality:

If a ≥ b and c < 0, then ac ≤ bc and a/c ≤ b/c.

If a ≤ b and c < 0, then ac ≥ bc and a/c ≥ b/c.
More generally, this applies for an ordered field; see #Ordered fields.
Additive inverse
The properties for the
additive inverse state:

For any real numbers a and b, negation inverts the inequality:

If a ≤ b, then − a ≥ − b.

If a ≥ b, then − a ≤ − b.
Multiplicative inverse
The properties for the multiplicative inverse state:

For any nonzero real numbers a and b that are both Positive number or both Negative number:

If a ≤ b, then 1/ a ≥ 1/ b.

If a ≥ b, then 1/ a ≤ 1/ b.

If one of a and b is positive and the other is negative, then:

If a < b, then 1/ a < 1/ b.

If a > b, then 1/ a > 1/ b.
These can also be written in chained notation as:

For any nonzero real numbers a and b:

If 0 < a ≤ b, then 1/ a ≥ 1/ b > 0.

If a ≤ b < 0, then 0 > 1/ a ≥ 1/ b.

If a < 0 < b, then 1/ a < 0 < 1/ b.

If 0 > a ≥ b, then 1/ a ≤ 1/ b < 0.

If a ≥ b > 0, then 0 < 1/ a ≤ 1/ b.

If a > 0 > b, then 1/ a > 0 > 1/ b.
Applying a function to both sides
Any monotonically increasing function may be applied to both sides of an inequality (provided they are in the domain of that function) and it will still hold. Applying a monotonically decreasing function to both sides of an inequality means the opposite inequality now holds. The rules for the additive inverse, and the multiplicative inverse for positive numbers, are both examples of applying a monotonically decreasing function.
If the inequality is strict ( a < b, a > b) and the function is strictly monotonic, then the inequality remains strict. If only one of these conditions is strict, then the resultant inequality is nonstrict. The rules for additive and multiplicative inverses are both examples of applying a strictly monotonically decreasing function.
A few examples of this rule are:

Exponentiating both sides of an inequality by n > 0 when a and b are positive real numbers:
 a ≤ b ⇔ a^{n} ≤ b^{n}.
 a ≤ b ⇔ a^{− n} ≥ b^{− n}.

Taking the natural logarithm to both sides of an inequality when a and b are positive real numbers:
 a ≤ b ⇔ ln( a) ≤ ln( b).
 a < b ⇔ ln( a) < ln( b).
 This is true because the natural logarithm is a strictly increasing function.
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:

a ≤ b implies a + c ≤ b + c;

0 ≤ a and 0 ≤ b implies 0 ≤ a × b.
Note that both ( Q, +, ×, ≤) and ( R, +, ×, ≤) are , but ≤ cannot be defined in order to make ( C, +, ×, ≤) an ordered field, because −1 is the square of i and would therefore be positive.
The nonstrict inequalities ≤ and ≥ on real numbers are . That is, given arbitrary a, b∈ R, at least one of a≤ b and b≤ a holds; at the same time, at least one of a≥ b and b≥ a holds. The strict inequalities < and > on real numbers are strict total orders. That is, < on R has trichotomy property: given arbitrary a, b∈ R, exactly one of a< b, b< a and a= b is true; likewise, > on R has the trichotomy property.
Chained notation
The notation
a < b < c stands for "
a <
b and
b <
c", from which, by the transitivity property above, it also follows that
a <
c. By the above laws, one can add or subtract the same number to all three terms, or multiply or divide all three terms by same nonzero number and reverse all inequalities if that number is negative. Hence, for example,
a <
b +
e <
c is equivalent to
a −
e <
b <
c −
e.
This notation can be generalized to any number of terms: for instance, a_{1} ≤ a_{2} ≤ ... ≤ a_{ n} means that a_{ i} ≤ a_{ i+1} for i = 1, 2, ..., n − 1. By transitivity, this condition is equivalent to a_{ i} ≤ a_{ j} for any 1 ≤ i ≤ j ≤ n.
When solving inequalities using chained notation, it is possible and sometimes necessary to evaluate the terms independently. For instance to solve the inequality 4 x < 2 x + 1 ≤ 3 x + 2, it is not possible to isolate x in any one part of the inequality through addition or subtraction. Instead, the inequalities must be solved independently, yielding x < 1/2 and x ≥ −1 respectively, which can be combined into the final solution −1 ≤ x < 1/2.
Occasionally, chained notation is used with inequalities in different directions, in which case the meaning is the logical conjunction of the inequalities between adjacent terms. For instance, a < b = c ≤ d means that a < b, b = c, and c ≤ d. This notation exists in a few programming languages such as Python.
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 ψ⇒φ holds, then ψ⇔φ also holds. For instance, the inequality ∀
a∈
real number.
a^{2} ≥ 0 is sharp, whereas the inequality ∀
a∈ℝ.
a^{2} ≥ −1 is not sharp.
Inequalities between means
There are many inequalities between means. For example, for any positive numbers
a_{1},
a_{2}, …,
a_{ n} we have where
 >
Power inequalities
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
 : $e^x\; \backslash ge\; 1+x.$
 : $(x^p\; \; 1)/p\; \backslash ge\; \backslash ln(x)\; \backslash ge\; (1\; \; \{1\}/\{x^p\})/p.$
 In the limit of p → 0, the upper and lower bounds converge to ln( x).
 : $x^x\; \backslash ge\; \backslash left(\; \backslash frac\{1\}\{e\}\backslash right)^\{1/e\}.$
 : $x^\{x^x\}\; \backslash ge\; x.$
 : $(x+y)^z\; +\; (x+z)^y\; +\; (y+z)^x\; >\; 2.$

For any real distinct numbers a and b,
 : $\backslash frac\{e^be^a\}\{ba\}\; >\; e^\{(a+b)/2\}.$

If x, y > 0 and 0 < p < 1, then
 : $x^p+y^p\; >\; (x+y)^p.$
 : $x^x\; y^y\; z^z\; \backslash ge\; (xyz)^\{(x+y+z)/3\}.$
 : $a^a\; +\; b^b\; \backslash ge\; a^b\; +\; b^a.$
 This inequality was solved by I.Ilani in JSTOR,AMM,Vol.97,No.1,1990.
 : $a^\{ea\}\; +\; b^\{eb\}\; \backslash ge\; a^\{eb\}\; +\; b^\{ea\}.$
 This inequality was solved by S.Manyama in AJMAA,Vol.7,Issue 2,No.1,2010 and by V.Cirtoaje in JNSA, Vol.4, Issue 2, 130–137, 2011.
 : $a^\{2a\}\; +\; b^\{2b\}\; +\; c^\{2c\}\; \backslash ge\; a^\{2b\}\; +\; b^\{2c\}\; +\; c^\{2a\}.$
 : $a^b\; +\; b^a\; >\; 1.$
 This result was generalized by R. Ozols in 2002 who proved that if a_{1}, ..., a_{ n} > 0, then
 : $a\_1^\{a\_2\}+a\_2^\{a\_3\}+\backslash cdots+a\_n^\{a\_1\}>1$
 (result is published in Latvian popularscientific quarterly The Starry Sky, see references).
Wellknown inequalities
often use inequalities to bound quantities for which exact formulas cannot be computed easily. Some inequalities are used so often that they have names:

Azuma's inequality

Bernoulli's inequality

Boole's inequality

Cauchy–Schwarz inequality

Chebyshev's inequality

Chernoff's inequality

Cramér–Rao inequality

Hoeffding's inequality

Hölder's inequality

Inequality of arithmetic and geometric means

Jensen's inequality

Kolmogorov's inequality

Markov's inequality

Minkowski inequality

Nesbitt's inequality

Pedoe's inequality

Poincaré inequality

Samuelson's inequality

Triangle inequality
Complex numbers and inequalities
The set of $\backslash mathbb\{C\}$ with its operations of addition and multiplication is a field, but it is impossible to define any relation ≤ so that $(\backslash mathbb\{C\},+,\backslash times,\backslash le)$ becomes an ordered field. To make $(\backslash mathbb\{C\},+,\backslash times,\backslash le)$ an ordered field, it would have to satisfy the following two properties:

if a ≤ b then a + c ≤ b + c

if 0 ≤ a and 0 ≤ b then 0 ≤ a b
Because ≤ is a total order, for any number a, either 0 ≤ a or a ≤ 0 (in which case the first property above implies that 0 ≤ − a). In either case 0 ≤ a^{2}; this means that $i^2>0$ and $1^2>0$; so $1>0$ and $1>0$, which means $(1+1)>0$; contradiction.
However, an operation ≤ can be defined so as to satisfy only the first property (namely, "if a ≤ b then a + c ≤ b + c"). Sometimes the lexicographical order definition is used:

$a\; \backslash le\; b$ if $\backslash mathrm\{Re\}(a)\; <\; \backslash mathrm\{Re\}(b)$ or $\backslash left(\backslash mathrm\{Re\}(a)\; =\; \backslash mathrm\{Re\}(b)\backslash right.$ and $\backslash left.\backslash mathrm\{Im\}(a)\; \backslash le\; \backslash mathrm\{Im\}(b)\backslash right)$
It can easily be proven that for this definition a ≤ b implies a + c ≤ b + c.
Vector inequalities
Inequality relationships similar to those defined above can also be defined for . If we let the vectors $x,y\backslash in\backslash mathbb\{R\}^n$ (meaning that $x\; =\; \backslash left(x\_1,x\_2,\backslash ldots,x\_n\backslash right)^\backslash mathsf\{T\}$ and $y\; =\; \backslash left(y\_1,y\_2,\backslash ldots,y\_n\backslash right)^\backslash mathsf\{T\}$ where $x\_i$ and $y\_i$ are real numbers for $i=1,\backslash ldots,n$), we can define the following relationships.

$x\; =\; y$ if $x\_i\; =\; y\_i$ for $i=1,\backslash ldots,n$

$x\; <\; y$ if $x\_i\; <\; y\_i$ for $i=1,\backslash ldots,n$

$x\; \backslash leq\; y$ if $x\_i\; \backslash leq\; y\_i$ for $i=1,\backslash ldots,n$ and $x\; \backslash neq\; y$

$x\; \backslash leqq\; y$ if $x\_i\; \backslash leq\; y\_i$ for $i=1,\backslash ldots,n$
Similarly, we can define relationships for $x\; >\; y$, $x\; \backslash geq\; y$, and $x\; \backslash geqq\; y$. We note that this notation is consistent with that used by Matthias Ehrgott in Multicriteria Optimization (see References).
The trichotomy property (as stated above) is not valid for vector relationships. For example, when $x\; =\; \backslash left^\backslash mathsf\{T\}$ and $y\; =\; \backslash left^\backslash mathsf\{T\}$, there exists no valid inequality relationship between these two vectors. Also, a multiplicative inverse would need to be defined on a vector before this property could be considered. However, for the rest of the aforementioned properties, a parallel property for vector inequalities exists.
General existence theorems
For a general system of polynomial inequalities, one can find a condition for a solution to exist. Firstly, any system of polynomial inequalities can be reduced to a system of quadratic inequalities by increasing the number of variables and equations (for example by setting a square of a variable equal to a new variable). A single quadratic polynomial inequality in n − 1 variables can be written as:
 $X^T\; A\; X\; \backslash geq\; 0$
where X is a vector of the variables $X=(x,y,z,\backslash ldots,1)^T$ and A is a matrix. This has a solution, for example, when there is at least one positive element on the main diagonal of A.
Systems of inequalities can be written in terms of matrices A, B, C, etc. and the conditions for existence of solutions can be written as complicated expressions in terms of these matrices. The solution for two polynomial inequalities in two variables tells us whether two conic section regions overlap or are inside each other. The general solution is not known but such a solution could be theoretically used to solve such unsolved problems as the kissing number problem. However, the conditions would be so complicated as to require a great deal of computing time or clever algorithms.
See also

Binary relation

Bracket (mathematics), for the use of similar ‹ and › signs as

Fourier–Motzkin elimination

Inclusion (set theory)

Inequation

Interval (mathematics)

List of inequalities

List of triangle inequalities

Partially ordered set

Relational operators, used in programming languages to denote inequality
Notes
External links