# Difference between revisions of "Set"

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==Power set== | ==Power set== | ||

− | The [[power set]] of a set <math>A</math>, denoted <math>\mathcal{P}(A)</math> is defined as the set of all its subsets. For example, the power set of <math>\{1,2,3\}</math> is <math>\{\{\},\{1\},\{2\},\{3\},\{1,2\},\{2,3\},\{1,3\},\{1,2,3\}\}</math>. If a <math>A</math> is a [[finite]] set of size <math>n</math> then <math>\mathcal{P}(A)</math> has size <math>2^n</math>. | + | The [[power set]] of a set <math>A</math>, denoted <math>\mathcal{P}(A)</math> is defined as the set of all its subsets. For example, the power set of <math>\{1,2,3\}</math> is <math>\{\{\},\{1\},\{2\},\{3\},\{1,2\},\{2,3\},\{1,3\},\{1,2,3\}\}</math>. If a <math>A</math> is a [[finite]] set of size <math>n</math> then <math>\mathcal{P}(A)</math> has size <math>2^n</math>, because <math>\sum_{i=0}^{n} {n\choose i} =2^n</math>. |

==Union and intersection== | ==Union and intersection== |

## Revision as of 14:36, 12 November 2006

*This article is a stub. Help us out by expanding it.*

The notion of a **set** is one of the fundamental notions in mathematics that has to be left undefined. Of course, we have plenty of synonyms for the word "set," like *collection, ensemble, group*, etc., but those names really do not define the meaning of the word *set*; all they can do is replace it in various sentences. So, instead of defining what sets are, one has to define what can be done with them or, in other words, what axioms the sets satisfy. These axioms are chosen to agree with our intuitive concept of a set, on one hand, and to allow various, sometimes quite sophisticated, mathematical constructions on the other hand. For the full collection of these axioms, see Zermelo-Fraenkel Axioms. In this article we shall present just a brief discussion of the most common properties of sets and operations related to them.

## Contents

## Relation of *belonging*

The most important property of sets is that, for every *object* and a set , we can say whether belongs to (written as ), or not (written as ). Two sets and are equal if they include the same objects, i.e., if for every object , we have if and only if .

## Specifying a set by listing its objects

This means that in order to indentify a particular set, it suffices to tell which objects belong to this set. If the set contains just several such objects, all you need to do is list them. So, you can specify the set consisting of the numbers , and , for example. (The standard notation for this set is . Note that the order in which the terms are listed is completely unimportant: we have to follow some order when writing things in one line, but you should actually imagine those numbers flowing freely inside those curly braces with no preference given to any of them. What matters is that these four numbers are in the set and everything else is out). But how do you specify sets that have very many (maybe infinitely many) elements? You cannot list them all even if you spend your entire life writing!

## Specifying a set by the common property of its elements

Another way to specify a set is to use some property to tell when an object belongs to this set. For instance, we may try to think (alas, only try!) of the set of all objects with green hair. In this case, we do not even try to list all such objects. We just decide that something belongs to this set if it has green hair and doesn't belong to it otherwise. This is a wonderful way to describe a set.

Unfortunately, this method has several potential pitfalls. It turns out, counter-intuitively, that not every collection of objects with a certain property is a set. The most famous example of this problem is Russell's Paradox: consider the property, "is a set and does not contain itself." (Remember that, given a set, we should be able to tell about **every** object whether it belongs to this set or not; in particular, we can ask this question about the set itself). The set specified by this property can neither belong, nor not belong to itself. There are a variety of ways to resolve this paradox, but the problem is clear: this way to describe sets should be used with extreme caution. One way to avoid this problem is as follows: given a property , choose a known set . Then the collection of elements of which have property will always be a set. (In particular, for our previous example to lead to a paradox, we would need to choose . However, it turns out that it can be proven that the set of all sets does not exist -- the collection of all sets is too big to be a set.)

## Subsets

We say that a set is a subset of a set if every object that belongs to also belongs to . This is denoted or . For example, the sets and are subsets of the set , but the set is not. Thus we can say that two sets are equal if and only if each is a subset of the other.

## Power set

The power set of a set , denoted is defined as the set of all its subsets. For example, the power set of is . If a is a finite set of size then has size , because .

## Union and intersection

The union of two or more sets is the set of all objects that belong to one or more of the sets. The union of A and B is denoted . For example, the union of and is . Unions can also be represented just as sums and products can be. would be the union of all sets that satisfy the statement. So, for example, would be the set of all natural numbers .

The intersection of two or more sets is the set of all objects that belong to all of the sets. The intersection of A and B is denoted . For example, the intersection of and is . Just like unions, intersections can be represented as such: . For example, , or the empty set defined next.

## Empty set

An empty set denoted is a set with no elements.

## Infinite sets

An infinite set can be defined as a set that has the same cardinality as one of its proper subsets. Alternatively, infinite sets are those which cannot be put into correspondence with any set of the form {1, 2, ..., n}.

## Cardinality

The cardinality of a set , denoted , is (informally) the size of the set. For a finite set, the cardinality is simply the number of elements. The empty set has cardinality 0.

iff there is a bijective function meaning that there is a function that maps all elements of to all the elements of with one-to-one correspondence.

iff there exists an injective function meaning there is a function that maps all elements of to (not necessarily all) elements of . can be defined similarily by expressing it as .

iff there exists an injective function and there is no bijective function meaning but . is defined similarly.

Although showing that and implies that is easy to prove when using finite sets, it is more complicated when using infinite sets. This theorem is called the Schroder-Bernstein Theorem and was proven by Schroder and Bernstein.

*To be continued*