Set (mathematics)

In mathematics, a set is a well-defined collection of distinct elements or members.[1][2][3] The elements that make up a set can be anything: people, letters of the alphabet, or mathematical objects, such as numbers, points in space, lines or other geometrical shapes, algebraic constants and variables, or other sets.[4] Two sets are equal if and only if they have precisely the same elements.[5] This is known as the axiom of extensionality.

This article is about what mathematicians call "intuitive" or "naive" set theory. For a more detailed account, see Naive set theory. For a rigorous modern axiomatic treatment of sets, see Set theory.
A set of polygons in an Euler diagram

Sets are ubiquitous in modern mathematics. The more specialized subject of set theory is part of the foundations of mathematics, from which nearly all of mathematics can be derived.[6]

Origin
Main article: Set theory

The concept of a set emerged in mathematics at the end of the 19th century.[7] The German word Menge, rendered as "set" in English, was coined by Bernard Bolzano in his work The Paradoxes of the Infinite.[8][9][10]

Passage with a translation of the original set definition of Georg Cantor. The German word Menge for set is translated with aggregate here.

Georg Cantor was one of the founders of set theory. He gave the following definition of a set at the beginning of his Beiträge zur Begründung der transfiniten Mengenlehre:[11]

A set is a gathering together into a whole of definite, distinct objects of our perception [Anschauung] or of our thought—which are called elements of the set.

Axiomatic set theory
Main article: Axiomatic set theory

A loose notion that allows any property without restriction define a collection, leads to paradoxes. Axiomatic set theory takes the concept of a "set" as a primitive notion, and the properties of sets are defined by axioms.[12] The most basic properties are that a set can have elements, and that two sets are equal (one set equals the other, so the two sets are in fact one and the same) if and only if every element of each set is an element of the other; this property is called the extensionality of sets.[13] The purpose of the axioms is to provide a basic framework from which to deduce the truth or not of particular mathematical propositions (statements) about sets.

How sets are defined and set notation

Mathematical texts commonly use capital letters[14][15][16] in italic such as A, B, C to denote sets.[16][17]

A set can be defined either intensionally, extensionally[18] or ostensively.

Semantic definition

The simplest intensional method of defining a set is by using a rule or semantic description:[19][18]

A is the set whose members are the first four positive integers.
B is the set of colors of the French flag.

Roster notation

Sets are not limited to collections of elements following simple rules, such as the sets in the examples above, however. Roster notation (or enumeration notation) is a method of defining a set by listing (or enumerating) the members of the set,[20][21][22][23][24] enclosing the list of members in curly brackets:

A = {4, 2, 1, 3}
B = {blue, white, red}.

This is an example of enumerative definition.

Unlike a sequence, a tuple or a permutation of a set, the order in which the elements of a set are listed in roster notation is irrelevant, so {6, 11} is the same set as {11, 6}, and {2, 6, 4}, {4, 2, 6}, {4, 6, 2}, {6, 2, 4} or {6, 4, 2} all represent the same set.[25][17][26]

For sets with many elements, especially those following an implicit pattern, the list of members can be abbreviated using ellipsis ("...").[27][28] For instance, the set of the first thousand positive integers may be specified in roster notation as:

{1, 2, 3, ..., 1000},

where the ellipsis indicates that the list continues by following the established pattern.[27]

Infinite sets in roster notation

Some sets have an endless list of elements. These are called infinite sets. For example, the set of integers, including positive, negative and zero, is an infinite set. In roster notation, this set can be written with just one ellipsis:

{0, 1, -1, 2, -2, 3, -3...}

or alternatively, using two:

{...-2, -1, 0, 1, 2, 3...}

Set-builder notation
Main article: Set-builder notation

Set-builder notation is another intensional method of describing a set, which is often found in mathematical texts.[18] The set is specified as a selection from a larger set, determined by a condition involving the elements.[29][30] For example, a set F can be defined as follows:

F

or:

F

In this notation, the vertical bar ("|") means "such that", and the description can be interpreted as "F is the set of all numbers n, such that n is an integer in the range from 0 to 19 inclusive". Some authors use a colon (":") instead of the vertical bar.[31]

Membership
Main article: Element (mathematics)

If B is a set and x is one of the objects of B, this is denoted as x ∈ B, and is read as "x is an element of B", as "x belongs to B", or "x is in B".[32] If y is not a member of B then this is written as y ∉ B, read as "y is not an element of B", or "y is not in B".[33][16][34]

For example, with respect to the sets A = {1, 2, 3, 4}, B = {blue, white, red}, and F = {n | n is an integer, and 0 ≤ n ≤ 19},

4 ∈ A and 12 ∈ F; and
20 ∉ F and green ∉ B.

The empty set
Main article: empty set

The empty set or null set, the set of no members, denoted { } or ∅, is unique.[35][16][36] Other notations are also in use (see empty set).[16]

Unit sets

A set with exactly one element, x, is a unit set, or singleton, {x}[5].

The set {x} is semantically distinct from the element x.[37] It can easily be proved that there is (at most) only one set that contains only itself as a member. However, defining other collections intensionally involving self-containment can quickly lead to paradox. (See Russell's paradox.)

Subsets
Main article: Subset

If every element of set A is also in B, then A is described as being a subset of B, or A is contained in B, written A ⊆ B.[38] B ⊇ A means B contains A, B includes A or B is a superset of A.[39][16] The relationship between sets established by ⊆ is called inclusion or containment. Two sets are equal if they contain each other: A ⊆ B and B ⊆ A is equivalent to A = B.[29]

If A is a subset of B, but A is not equal to B, then A is called a proper subset of B. This can be written A ⊊ B. Likewise, B ⊋ A means B is a proper superset of A, i.e. B contains A, and is not equal to A.

A third pair of operators ⊂ and ⊃ are used differently by different authors: some authors use A ⊂ B and B ⊃ A to mean A is any subset of B (and not necessarily a proper subset),[40][33] while others reserve A ⊂ B and B ⊃ A for cases where A is a proper subset of B[38]

Examples:

  • The set of all humans is a proper subset of the set of all mammals.
  • {1, 3} ⊂ {1, 2, 3, 4}.
  • {1, 2, 3, 4} ⊆ {1, 2, 3, 4}.

The empty set is a subset of every set,[41] and every set is a subset of itself:[42]

  • ∅ ⊆ A.
  • A ⊆ A.

Euler and Venn diagrams
A is a subset of B

An Euler diagram is a graphical representation of a set as a closed loop, enclosing its elements, or the relationships between different sets, as closed loops. If two sets have no members in common, the loops do not overlap.

This is distinct from a Venn diagram, which shows all possible relations between two or more sets, with each loop overlapping the others.

Partitions
Main article: Partition of a set

A partition of a set S is a set of nonempty subsets of S, such that every element x in S is in exactly one of these subsets. That is, the subsets are pairwise disjoint (meaning any two sets of the partition contain no element in common), and the union of all the subsets of the partition is S.[43][44]

Power sets
Main article: Power set

The power set of a set S is the set of all subsets of S.[29] The power set contains S itself and the empty set because these are both subsets of S. For example, the power set of the set {1, 2, 3} is {{1, 2, 3}, {1, 2}, {1, 3}, {2, 3}, {1}, {2}, {3}, ∅}. The power set of a set S is usually written as P(S).[29][45][16][17]

The power set of a finite set with n elements has 2n elements.[46] For example, the set {1, 2, 3} contains three elements, and the power set shown above contains 23 = 8 elements.

The power set of an infinite (either countable or uncountable) set is always uncountable. Moreover, the power set of a set is always strictly "bigger" than the original set, in the sense that there is no way to pair every element of S with exactly one element of P(S). (There is never an onto map or surjection from S onto P(S).)[47]

Cardinality
Main article: Cardinality

The cardinality of a set S, denoted |S|, is the number of members of S.[48] For example, if B = {blue, white, red}, then |B| = 3. Repeated members in roster notation are not counted,[49][50] so |{blue, white, red, blue, white}| = 3, too.

The cardinality of the empty set is zero.[51]

Infinite sets and infinite cardinality

Some sets have infinite cardinality. The set N of natural numbers, for instance, is infinite.[29] Some infinite cardinalities are greater than others. For instance, the set of real numbers has greater cardinality than the set of natural numbers.[52] However, it can be shown that the cardinality of a straight line (i.e., the number of points on a line) is the same as the cardinality of any segment of that line, of the entire plane, and indeed of any finite-dimensional Euclidean space.[53]

Special sets
The natural numbers ℕ are contained in the integers ℤ, which are contained in the rational numbers ℚ, which are contained in the real numbers ℝ, which are contained in the complex numbers ℂ

There are sets of such mathematical importance, to which mathematicians refer so frequently, that they have acquired special names and notational conventions to identify them.

Many of these important sets are represented in mathematical texts using bold (e.g. P) or blackboard bold (e.g. ℙ) typeface.[54] These include:[16]

  • P or ℙ, denoting the set of all primes: P = {2, 3, 5, 7, 11, 13, 17, ...}[55]
  • N or ℕ, denoting the set of all natural numbers: N = {0, 1, 2, 3, ...} (some authors exclude 0)[54]
  • Z or ℤ, denoting the set of all integers (whether positive, negative or zero): Z = {..., −2, −1, 0, 1, 2, ...}[54]
  • Q or ℚ, denoting the set of all rational numbers (that is, the set of all proper and improper fractions): Q = {a/b | a, b ∈ Z, b ≠ 0}, for example, 1/4 ∈ Q and 11/6 ∈ Q, and since every integer a can be expressed as the fraction a/1, all integers are members of this set (Z ⊊ Q)[54]
  • R or ℝ, denoting the set of all real numbers, including all rational numbers, together with all irrational numbers (that is, algebraic numbers that cannot be rewritten as fractions such as √2, as well as transcendental numbers such as π, e)[54]
  • C or ℂ, denoting the set of all complex numbers: C = {a + bi | a, b ∈ R}, for example, 1 + 2i ∈ C[54]
  • H or ℍ, denoting the set of all quaternions: H = {a + bi + cj + dk | a, b, c, d ∈ R}, for example, 1 + i + 2j − k ∈ H[56]
Further information: Blackboard_bold § Usage

Each of the above sets of numbers has an infinite number of elements, and each can be considered to be a proper subset of the sets listed below it. The primes are used less frequently than the others outside of number theory and related fields.

Positive and negative sets are sometimes denoted by superscript plus and minus signs, respectively. For example, ℚ+ represents the set of positive rational numbers.

Basic operations
Main article: Algebra of sets

There are several fundamental operations for constructing new sets from given sets.

Unions
The union of A and B, denoted A ∪ B
Main article: Union (set theory)

Two sets can be "added" together. The union of A and B, denoted by A ∪ B,[16] is the set of all things that are members of either A or B.

Examples:

  • {1, 2} ∪ {1, 2} = {1, 2}.
  • {1, 2} ∪ {2, 3} = {1, 2, 3}.
  • {1, 2, 3} ∪ {3, 4, 5} = {1, 2, 3, 4, 5}

Some basic properties of unions:

  • A ∪ B = B ∪ A.
  • A ∪ (B ∪ C) = (A ∪ B) ∪ C.
  • A ⊆ (A ∪ B).
  • A ∪ A = A.
  • A ∪ ∅ = A.
  • A ⊆ B if and only if A ∪ B = B.

Intersections
Main article: Intersection (set theory)

A new set can also be constructed by determining which members two sets have "in common". The intersection of A and B, denoted by A ∩ B,[16] is the set of all things that are members of both A and B. If A ∩ B = ∅, then A and B are said to be disjoint.

The intersection of A and B, denoted A ∩ B.

Examples:

  • {1, 2} ∩ {1, 2} = {1, 2}.
  • {1, 2} ∩ {2, 3} = {2}.
  • {1, 2} ∩ {3, 4} = ∅.

Some basic properties of intersections:

  • A ∩ B = B ∩ A.
  • A ∩ (B ∩ C) = (A ∩ B) ∩ C.
  • A ∩ B ⊆ A.
  • A ∩ A = A.
  • A ∩ ∅ = ∅.
  • A ⊆ B if and only if A ∩ B = A.

Complements
The relative complement
of B in A
The complement of A in U
The symmetric difference of A and B
Main article: Complement (set theory)

Two sets can also be "subtracted". The relative complement of B in A (also called the set-theoretic difference of A and B), denoted by A \ B (or A − B),[16] is the set of all elements that are members of A, but not members of B. It is valid to "subtract" members of a set that are not in the set, such as removing the element green from the set {1, 2, 3}; doing so will not affect the elements in the set.

In certain settings, all sets under discussion are considered to be subsets of a given universal set U. In such cases, U \ A is called the absolute complement or simply complement of A, and is denoted by A′ or Ac.[16]

  • A′ = U \ A

Examples:

  • {1, 2} \ {1, 2} = ∅.
  • {1, 2, 3, 4} \ {1, 3} = {2, 4}.
  • If U is the set of integers, E is the set of even integers, and O is the set of odd integers, then U \ E = E′ = O.

Some basic properties of complements include the following:

  • A \ B ≠ B \ A for A ≠ B.
  • A ∪ A′ = U.
  • A ∩ A′ = ∅.
  • (A′)′ = A.
  • ∅ \ A = ∅.
  • A \ ∅ = A.
  • A \ A = ∅.
  • A \ U = ∅.
  • A \ A′ = A and A′ \ A = A′.
  • U′ = ∅ and ∅′ = U.
  • A \ B = A ∩ B′.
  • if A ⊆ B then A \ B = ∅.

An extension of the complement is the symmetric difference, defined for sets A, B as

For example, the symmetric difference of {7, 8, 9, 10} and {9, 10, 11, 12} is the set {7, 8, 11, 12}. The power set of any set becomes a Boolean ring with symmetric difference as the addition of the ring (with the empty set as neutral element) and intersection as the multiplication of the ring.

Cartesian product
Main article: Cartesian product

A new set can be constructed by associating every element of one set with every element of another set. The Cartesian product of two sets A and B, denoted by A × B,[16] is the set of all ordered pairs (a, b) such that a is a member of A and b is a member of B.

Examples:

  • {1, 2} × {red, white, green} = {(1, red), (1, white), (1, green), (2, red), (2, white), (2, green)}.
  • {1, 2} × {1, 2} = {(1, 1), (1, 2), (2, 1), (2, 2)}.
  • {a, b, c} × {d, e, f} = {(a, d), (a, e), (a, f), (b, d), (b, e), (b, f), (c, d), (c, e), (c, f)}.

Some basic properties of Cartesian products:

  • A × ∅ = ∅.
  • A × (B ∪ C) = (A × B) ∪ (A × C).
  • (A ∪ B) × C = (A × C) ∪ (B × C).

Let A and B be finite sets; then the cardinality of the Cartesian product is the product of the cardinalities:

  • | A × B | = | B × A | = | A | × | B |.

Applications

Set theory is seen as the foundation from which virtually all of mathematics can be derived. For example, structures in abstract algebra, such as groups, fields and rings, are sets closed under one or more operations.

One of the main applications of naive set theory is in the construction of relations. A relation from a domain A to a codomain B is a subset of the Cartesian product A × B. For example, considering the set S = { rock, paper, scissors } of shapes in the game of the same name, the relation "beats" from S to S is the set B = { (scissors,paper), (paper,rock), (rock,scissors) }; thus x beats y in the game if the pair (x,y) is a member of B. Another example is the set F of all pairs (x, x2), where x is real. This relation is a subset of R' × R, because the set of all squares is subset of the set of all real numbers. Since for every x in R, one and only one pair (x,...) is found in F, it is called a function. In functional notation, this relation can be written as F(x) = x2.

Axiomatic set theory
Main article: Axiomatic set theory

Although initially naive set theory, which defines a set merely as any well-defined collection, was well accepted, it soon ran into several obstacles. It was found that this definition spawned several paradoxes, most notably:

  • Russell's paradox – It shows that the "set of all sets that do not contain themselves," i.e. the "set" {x|x is a set and x ∉ x} does not exist.
  • Cantor's paradox – It shows that "the set of all sets" cannot exist.

The reason is that the phrase well-defined is not very well-defined. It was important to free set theory of these paradoxes, because nearly all of mathematics was being redefined in terms of set theory. In an attempt to avoid these paradoxes, set theory was axiomatized based on first-order logic, and thus axiomatic set theory was born.

For most purposes, however, naive set theory is still useful.

Principle of inclusion and exclusion
Main article: Inclusion–exclusion principle
The inclusion-exclusion principle can be used to calculate the size of the union of sets: the size of the union is the size of the two sets, minus the size of their intersection.

The inclusion–exclusion principle is a counting technique that can be used to count the number of elements in a union of two sets—if the size of each set and the size of their intersection are known. It can be expressed symbolically as

A more general form of the principle can be used to find the cardinality of any finite union of sets:

De Morgan's laws

Augustus De Morgan stated two laws about sets.

If A and B are any two sets then,

  • (A ∪ B)′ = A′ ∩ B′

The complement of A union B equals the complement of A intersected with the complement of B.

  • (A ∩ B)′ = A′ ∪ B′

The complement of A intersected with B is equal to the complement of A union to the complement of B.

See also

Notes
  1. P. K. Jain; Khalil Ahmad; Om P. Ahuja (1995). Functional Analysis. New Age International. p. 1. ISBN 978-81-224-0801-0.
  2. Samuel Goldberg (1 January 1986). Probability: An Introduction. Courier Corporation. p. 2. ISBN 978-0-486-65252-8.
  3. Thomas H.. Cormen; Thomas H Cormen; Charles E Leiserson; Ronald L Rivest; Clifford Stein (2001). Introduction To Algorithms. MIT Press. p. 1070. ISBN 978-0-262-03293-3.
  4. Halmos 1960, p. 1
  5. Stoll, Robert (1974). Sets, Logic and Axiomatic Theories. W. H. Freeman and Company. pp. 5.
  6. Paul R. Halmos (19 April 2017). Naive Set Theory. Courier Dover Publications. p. 1. ISBN 978-0-486-81487-2.
  7. José Ferreirós (16 August 2007). Labyrinth of Thought: A History of Set Theory and Its Role in Modern Mathematics. Birkhäuser Basel. ISBN 978-3-7643-8349-7.
  8. Steve Russ (9 December 2004). The Mathematical Works of Bernard Bolzano. OUP Oxford. ISBN 978-0-19-151370-1.
  9. William Ewald; William Bragg Ewald (1996). From Kant to Hilbert Volume 1: A Source Book in the Foundations of Mathematics. OUP Oxford. p. 249. ISBN 978-0-19-850535-8.
  10. Paul Rusnock; Jan Sebestík (25 April 2019). Bernard Bolzano: His Life and Work. OUP Oxford. p. 430. ISBN 978-0-19-255683-7.
  11. "Eine Menge, ist die Zusammenfassung bestimmter, wohlunterschiedener Objekte unserer Anschauung oder unseres Denkens – welche Elemente der Menge genannt werden – zu einem Ganzen." "Archived copy". Archived from the original on 2011-06-10. Retrieved 2011-04-22.CS1 maint: archived copy as title (link)
  12. Jose Ferreiros (1 November 2001). Labyrinth of Thought: A History of Set Theory and Its Role in Modern Mathematics. Springer Science & Business Media. ISBN 978-3-7643-5749-8.
  13. Halmos 1960, p. 2
  14. Seymor Lipschutz; Marc Lipson (22 June 1997). Schaum's Outline of Discrete Mathematics. McGraw Hill Professional. p. 1. ISBN 978-0-07-136841-4.
  15. Halmos 1960, p. 1
  16. "Comprehensive List of Set Theory Symbols". Math Vault. 2020-04-11. Retrieved 2020-08-19.
  17. "Introduction to Sets". www.mathsisfun.com. Retrieved 2020-08-19.
  18. Frank Ruda (6 October 2011). Hegel's Rabble: An Investigation into Hegel's Philosophy of Right. Bloomsbury Publishing. p. 151. ISBN 978-1-4411-7413-0.
  19. Halmos 1960, p. 4
  20. Charles Roberts (24 June 2009). Introduction to Mathematical Proofs: A Transition. CRC Press. p. 45. ISBN 978-1-4200-6956-3.
  21. David Johnson; David B. Johnson; Thomas A. Mowry (June 2004). Finite Mathematics: Practical Applications (Docutech Version). W. H. Freeman. p. 220. ISBN 978-0-7167-6297-3.
  22. Charles Roberts (24 June 2009). Introduction to Mathematical Proofs: A Transition. CRC Press. p. 45. ISBN 978-1-4200-6956-3.
  23. Ignacio Bello; Anton Kaul; Jack R. Britton (29 January 2013). Topics in Contemporary Mathematics. Cengage Learning. p. 47. ISBN 1-133-10742-7.
  24. Susanna S. Epp (4 August 2010). Discrete Mathematics with Applications. Cengage Learning. p. 13. ISBN 0-495-39132-8.
  25. Stephen B. Maurer; Anthony Ralston (21 January 2005). Discrete Algorithmic Mathematics. CRC Press. p. 11. ISBN 978-1-4398-6375-6.
  26. D. Van Dalen; H. C. Doets; H. De Swart (9 May 2014). Sets: Naïve, Axiomatic and Applied: A Basic Compendium with Exercises for Use in Set Theory for Non Logicians, Working and Teaching Mathematicians and Students. Elsevier Science. p. 1. ISBN 978-1-4831-5039-0.
  27. Alfred Basta; Stephan DeLong; Nadine Basta (1 January 2013). Mathematics for Information Technology. Cengage Learning. p. 3. ISBN 1-285-60843-7.
  28. Laura Bracken; Ed Miller (15 February 2013). Elementary Algebra. Cengage Learning. p. 36. ISBN 0-618-95134-2.
  29. John F. Lucas (1990). Introduction to Abstract Mathematics. Rowman & Littlefield. p. 108. ISBN 978-0-912675-73-2.
  30. Weisstein, Eric W. "Set". mathworld.wolfram.com. Retrieved 2020-08-19.
  31. Ralph C. Steinlage (1987). College Algebra. West Publishing Company. ISBN 978-0-314-29531-6.
  32. Halmos 1960, p. 2
  33. Marek Capinski; Peter E. Kopp (2004). Measure, Integral and Probability. Springer Science & Business Media. p. 2. ISBN 978-1-85233-781-0.
  34. "Set Symbols". www.mathsisfun.com. Retrieved 2020-08-19.
  35. Halmos 1960, p. 8
  36. K.T. Leung; Doris Lai-chue Chen (1 July 1992). Elementary Set Theory, Part I/II. Hong Kong University Press. p. 27. ISBN 978-962-209-026-2.
  37. Halmos 1960, Sect.2 Halmos remarks that box containing a hat is not the same as a hat.
  38. Felix Hausdorff (2005). Set Theory. American Mathematical Soc. p. 30. ISBN 978-0-8218-3835-8.
  39. Peter Comninos (6 April 2010). Mathematical and Computer Programming Techniques for Computer Graphics. Springer Science & Business Media. p. 7. ISBN 978-1-84628-292-8.
  40. Halmos 1960, p. 3
  41. Halmos 1960, p. 8
  42. Halmos 1960, p. 3
  43. Toufik Mansour (27 July 2012). Combinatorics of Set Partitions. CRC Press. ISBN 978-1-4398-6333-6.
  44. Halmos 1960, p. 28
  45. Halmos 1960, p. 19
  46. Halmos 1960, p. 20
  47. Edward B. Burger; Michael Starbird (18 August 2004). The Heart of Mathematics: An invitation to effective thinking. Springer Science & Business Media. p. 183. ISBN 978-1-931914-41-3.
  48. Yiannis N. Moschovakis (1994). Notes on Set Theory. Springer Science & Business Media. ISBN 978-3-540-94180-4.
  49. Arthur Charles Fleck (2001). Formal Models of Computation: The Ultimate Limits of Computing. World Scientific. p. 3. ISBN 978-981-02-4500-9.
  50. William Johnston (25 September 2015). The Lebesgue Integral for Undergraduates. The Mathematical Association of America. p. 7. ISBN 978-1-939512-07-9.
  51. Karl J. Smith (7 January 2008). Mathematics: Its Power and Utility. Cengage Learning. p. 401. ISBN 0-495-38913-7.
  52. John Stillwell (16 October 2013). The Real Numbers: An Introduction to Set Theory and Analysis. Springer Science & Business Media. ISBN 978-3-319-01577-4.
  53. David Tall (11 April 2006). Advanced Mathematical Thinking. Springer Science & Business Media. p. 211. ISBN 978-0-306-47203-9.
  54. George Tourlakis (13 February 2003). Lectures in Logic and Set Theory: Volume 2, Set Theory. Cambridge University Press. p. 137. ISBN 978-1-139-43943-5.
  55. Abhijit Das (19 April 2016). Computational Number Theory. CRC Press. p. 2. ISBN 978-1-4822-0582-4.
  56. D.L. Johnson (6 December 2012). Elements of Logic via Numbers and Sets. Springer Science & Business Media. p. 165. ISBN 978-1-4471-0603-6.

References
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.