## Elementary Set Theory## Philip J. Erdelsky## July 20, 2010 |

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Most, if not all, of pure mathematics is couched in the language of sets. You may notice that this section contains many definitions and only a few theorems. However, even a definition can contain a lot of mathematical wisdom. It took mathematicians centuries to formulate some fundamental definitions.

A __set__ is a collection of items considered as a whole. If there are
only a few items, the set can be defined by listing them in braces.
For example, the set *A* might be defined as follows:

A = {1,2,3}

The items in a set are called __elements__ or __members__ of the set.
They are also said to __belong__ to the set or to be __in__ the set,
and the set is said to
__contain__ them. The symbol *∈ * is used to express
this relationship -- *a∈ A*
means *a* belongs to *A*, and
*a∉ A* means *a* does not
belong to *A*.

Two sets are equal if they contain exactly the same elements. That is,
set *A* is equal to set *B* if every element of *A* is also
an element of *B*, and
every element of *B* is also an element of *A*. The order in which the elements of
a set are listed in its definition is irrelevant. For example, the
sets *{1,2,3}* and *{3,2,1}* are equal.

An element cannot belong to a set more than once. Therefore, when a set is defined by listing its elements, each element is listed only once.

A set that contains no elements is called the __empty__ set, and is
represented by the symbol *∅*.

If every element of the set *A* is also an element of the set *B*,
then *A* is
said to be a __subset__ of *B*, represented symbolically by
*A⊆ B*, or *B* is said to __include__ *A*.
Every set is a subset of itself, and the
empty set is a subset of every set.

If *A⊆ B* and there is at least one
element of *B* that is not an
element of *A*, then *A* is said to be a __proper__ subset of *B*,
represented symbolically by
*A⊂ B*.

A subset is often defined by some property of its elements.
For example, let *A = {1,2,3,4,5,6}*, and let
*B = {2,4,6}*. Then *B* could be defined as the set of all
elements of *A* which are
even, or in symbols:

B ={x∈ A | xis even}.

Here the symbol | means "such that". The word "all" is understood. In some cases
the set *A* may also be understood.

The __intersection__ of any number of sets is the set of elements that they
all have in common. For example, the intersection of *{1,2,3,4,5}*,
*{2,3,4,5,6,7,8,9}* and *{3,5,7,9}* is *{3,5}*. It is clear that the intersection
of a collection of sets is a subset of every set in the collection.
The intersection of two sets *A* and *B* is represented symbolically by
*A∩B*.

The intersection operation has several obvious properties:

- Commutativity:
*A∩B = B∩A*. - Associativity:
*(A∩B)∩C = A∩(B∩C)*. *A∩B = A*if, and only if,*A⊆ B*.

The __union__ of any number of sets is the set of all of their elements.
For example the union of *{1,2,3,4,5}*,
*{2,3,4,5,6,7,8,9}* and *{3,5,7,9}* is *{1,2,3,4,5,6,7,8,9}*. It is clear that
every set in a union is a subset of their union.
The union of two sets *A* and *B* is represented symbolically by
*A∪B*.

The union operation has several obvious properties:

- Commutativity:
*A∪B = B∪A*. - Associativity:
*(A∪B)∪C = A∪(B∪C)*. *A∪B = B*if, and only if,*A⊆ B*.

Two sets are said to be __disjoint__ if they have no elements in common;
i.e., *A* and *B* are disjoint if
*A∩B = ∅*. Three or more sets are said to be
disjoint if every two of them are disjoint.

The notation *A-B* is used to indicate the set of all elements of
*A* that are
not elements of *B*. This operation has no standard name, but when
*B* is a subset
of *A*, *A-B* is sometimes said to be the __complement__ of
*B* in *A*.

The relationships among sets are often represented pictorially by
a __Venn diagram__, in which sets are represented as the interiors
of overlapping circles (or other plane figures). Set combinations
are represented by areas bounded by the circles, as shown in the following
example for two sets:

An __ordered pair__ is a set of two elements in a specified order.
An ordered pair is usually written *(a,b)* where *a* is the first element and
*b* is the second element. Two ordered pairs *(a,b)* and
*(c,d)* are equal
if *a=c* and *b=d*. Reversing the elements of an ordered
pair produces a different ordered pair if the elements are not the same.
For example, the ordered pair *(1,2)* is not equal to the
ordered pair *(2,1)*.

For two sets *A* and *B*, the __cross product__
*A⨯ B* is the set of all ordered
pairs whose first and second elements are elements of *A* and *B*, respectively.
That is,

A⨯ B = {(a,b) ∣ a∈ Aandb∈ B}

Ordered triples, quadruples, etc. could be defined, but they are seldom needed.

A __relation__ *R* on a set *A* is simply a set of ordered pairs of elements of
*A*, i.e., *R ⊆ A⨯ A*.
Two elements *a* and *b* are said to obey the
relation if *(a,b)* is in *R*. However, for most relations, the set notation is
not used. Instead, a symbol such as *~* placed between the elements to indicate
that they obey the relation; for example *a~b* means that
*(a,b)* is in *R*.

Other symbols often used for relations are

= > < ≥ ≤ ∣ ≠ ⊃ ⊂ ⊇ ⊆ ≡

Most useful relations have some additional properties.
A relation *~* on the set *A* is an __equivalence__ if the
following hold for every *a*, *b* and *c* in *A*:

- It is
__reflexive__:*a~a*. - It is
__symmetric__:*a~b*implies that*b~a*. - It is
__transitive__:*a~b*and*b~c*imply that*a~c*.

A set of nonempty subsets of a set *A* is called a __partition__ of *A* if each element
of *A* belongs to one and only one of the subsets; i.e., if the subsets
are disjoint and their union is *A*. The following theorem establishes
a connection between an equivalence relation and a partition.

**Theorem 3.1.** *If ~ is an equivalence relation on the set A, then there
is partition of the set A such that a~b if, and only if, a and b
belong to the same set in the partition. Conversely, if P is a partition
of A, then "a and b belong to the same set in P" is an equivalence
relation.*

*Proof.* Consider the set *P* of subsets
*T _{a} = {x ∈ A | x~a}*. Clearly every

Now let *T _{a}* and

The converse is trivial. █

The sets in the partition associated in this way with an equivalence
relation are called its __equivalence classes__. They are often
used to define mathematical systems.

Equivalence relations on two sets *A*
and *B* can be used to define an equivalence
relation on *A⨯ B* in
the obvious way: *(a,b)* is equivalent to
*(c,d)* if *a*
is equivalent to *c* and *b*
is equivalent to *d*.

A __partial order__ on a set *A* is a relation ≤ with the following
properties for every *a*, *b* and *c* in *A*:

- It is
__reflexive__:*a ≤ a*. - It is
__antisymmetric__:*a ≤ b*and*b ≤ a*imply that*a = b*. - It is
__transitive__: a*≤ b*and*b ≤ c*imply that*a ≤ c*.

A partial order ≤ on the set *A* is called a __linear order__
(or a __total order__) if, for every two elements *a* and *b*
of *A*,
*a ≤ b* or *b ≤ a*
(or both, if *a = b*).

The set of all subsets of a set is partially ordered by inclusion:
*S ≤ T* means *S⊆ T*.
This partial order is usually not a total
order because we can find two subsets, such as *{1,2,3}* and
*{2,3,4}*,
such that neither is a subset of the other.

The familiar relation ≤ in arithmetic is a total order.

In working with a partial or total order, it is common to define some associated relations:

*a ≥ b*means*b ≤ a*,*a < b*means*a ≤ b*and*a ≠ b*,*a > b*means*b ≤ a*and*b ≠ a*.

There is an alternative way to define partial and total orders. A relation < is a partial order if obeys the following two conditions:

- It is transitive:
*a < b*and*b < c*imply that*a < c*. *a < a*is always false.

A partial order is a total order if it is also __trichotomous__:
for any two elements a and b, one and only one of the following holds:

*a < b*,*a = b*,*b < a*.

The other relations are then defined in terms of *<*:

*a ≤ b*means*a < b*or*a = b*.*a ≥ b*means*b < a*or*a = b*.*a > b*means*b < a*.

It can be shown that the two ways of defining partial and total orders are equivalent.

Generally, the names "partial order" and "total order" are applied to
the entire set of relations ≤, *<*, *>* and ≥ without specifying which
is the order relation and which are associated with it.

A __function__ *f* from the set *A* to the set *B* is a rule which, given
any element *x* of *A*, produces exactly one corresponding
element of *B*
represented by *f(x)*. This concept is often expressed symbolically as
*f:A⟶B*.

A function is also called a __mapping__. Both names are commonly used in
mathematics, but from this point forth we will use the name function.

A second, and more abstract, way to define a function
*f:A⟶B* is as
subset of *A ⨯ B* such that for every element
*x* of *A* there is one
and only one ordered pair in the subset whose first element is *x*. The second
element of the pair is then defined to be *f(x)*.

The element *f(x)* is
called the __image__ of *x* under the function. The function *f*
is also said to __map__ or __carry__ the element *x* to the element
*f(x)*.

If *f:A⟶B* then *A* is called the __domain__
of *f*, and the set of
all elements of *B* which are images of elements in *A* is called the __range__
of *f*. The sets *A* and *B* need not be different; in fact, they are the same
in many applications.

Some functions have special properties that make them especially interesting
or useful. If *f:A⟶B*, then

If the range is equal to

B, thenfis called asurjection, asurjectivefunction, or a function ofAontoB. The function is sometimes also said to be "onto", but the use of a preposition as an adjective sounds so stilted that good writers tend to avoid it.If the range is a proper subset of

B, thenfis called a function ofAintoB.If the

fcarries at most one element of its domain into each element of its range, i.e., iff(x) = f(y)implies thatx = y, thenfis called aninjection, aninjective function, or aone-to-onefunction.If

fis both surjective and one-to-one then it is called aone-to-one correspondenceofAandB. Iffis one-to-one but not surjective, then it is a one-to-one correspondence ofAand its range, which is a proper subset ofB.

If *f:A⟶B* is a one-to-one correspondence then
it has an __inverse__
function called *f ^{ -1}:B⟶A* defined by

fthe element^{ -1}(x) =wofAsuch thatf(w) = x.

Of course, the converse is also true. If a function has an inverse, then it is a one-to-one correspondence.

Two functions *f:A⟶B* and
*g:A⟶B* are equal if *f(x) = g(x)*
for every *x* in *A*.

If the range of one function is a subset of the domain of another, then a
__composite__ function is defined by applying the functions successively.
That is, if *f:A⟶B* and
*g:B⟶C* then the
composite function *(f◌g):A⟶C* is defined by

(f ◌g)(x) = g(f(x))for everyxinA.

If the functions have appropriate domains and ranges, composition is
associative, i.e, *(f ◌g) ◌h =
f ◌(g ◌h)*.

A one-to-one function *f:A⟶B* of two sets
with some structure is called an __isomorphism__ if it preserves
the structure. We have seen one example of a set with structure:
the partially ordered set. If the sets *A* and *B* are
partially ordered, then *f:A⟶B* is
an isomorphism if it is one-to-one, surjective, and
*f(x) < f(y)* if, and only if, *x < y*.

An isomorphism of a structured set with itself is called an
__automorphism__. Clearly, the identity function (*f(x) = x*
for all *x*) is an automorphism of any structured set. A good
example of a nontrivial automorphism is the function which carries
a complex number into its conjugate (i.e,. *f(x+iy) = x-iy* for
all real *x* and *y*). It is one-to-one, surjective, and
preserves addition and multiplication of complex numbers.

Suppose *f:A⟶B* and
there are equivalence relations on the sets *A* and
*B*. Let *P _{A}* and

A __unary operation__ on a set is a function whose domain is that set.
What distinguishes a unary operation from an ordinary function is the
notation used, and often its relationships with other functions or
operations. For example, the function that carries any real number
*x*
to the number *-x* is a unary operation
called __negation__.
The range of the function is often the same set, but this is not
required.

A __binary operation__ is a function whose domain is the
cross product of two sets (or the cross product of a set with itself).
For example, addition and multiplication are two binary operations
on the set *R⨯ R*, where *R* is the set
of real numbers. The image of an ordered pair *(x,y)* is usually
written as *x+y* for addition and *xy* for multiplication.
Here *x* and *y* are called the __operands__.
The former notation is usually used only for addition, or operations
very much like addition. The latter notation is used for more general
operations.

Unary and binary operations are very common in mathematics; operations with three or more operands are rare, except for extensions of binary operations as noted below. Binary operations on a single set are more common than binary operations on pairs of sets, but both are encountered frequently.

A binary operation is said to be __associative__ if it can be used
on three operands without regard to their grouping, i.e., if

(xy)z = x(yz)

(x + y) + z = x + (y + z)

If a binary operation is associative, we can write the result for three operands without parentheses, making it a well-defined operation with three operands:

xyz = (xy)z = x(yz)

x + y + z = (x + y) + z = x + (y + z)

Ordinary addition and multiplication are associative; so are many other binary operations. The composition of functions is an associative binary operation (provided the functions have suitable domains and ranges). In fact, most binary operations are associative.

If a binary operation is associative, it is easy to extend the property to operations on four or more operands:

wxyz = (wxy)z = (w(xy))z = w((xy)z) = w(xyz).

A binary operation is __commutative__ if the order of the operands
does not affect the result; i.e., if

xy = yx

x + y = y + x

If a commutative operation is also associative, commutativity can easily be extended to operations on three or more operands:

xyz = (xy)z = (yx)z = yxz = y(xz) = (yx)z = yxz, etc.

Binary operations which are commutative but not associative are very rare. Binary operations which are associative but not commutative are fairly common. Composition of functions is one example; a demonstration of that fact will be given later.

Now consider a binary operation on
*A⨯ B* with its range
in *C* (which need not be different sets).
Suppose there are equivalence operations on these sets (which also
need not be different), and the binary operation preserves
equivalence, *i.e.*, the operation when applied to equivalent
operands gives equivalent results, or *a ~ b*
and *c ~ d* imply that
*ac ~ bd*. Then, just as a function of one
variable was extended to a function on equivalence classes, an
operation on two variables can be extended similarly. If
*a* and *b* are any
elements of the equivalence classes *P*
and *Q*, respectively, then
*PQ* is defined to be the equivalence class
containing *ab*. The new operation inherits
many properties of the old one, including associativity and commutativity.

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