Set (mathematics) Information
A set is the mathematical model for a collection of different^{ [1]} things;^{ [2]}^{ [3]}^{ [4]} a set contains elements or members, which can be mathematical objects of any kind: numbers, symbols, points in space, lines, other geometrical shapes, variables, or even other sets.^{ [5]} The set with no element is the empty set; a set with a single element is a singleton. A set may have a finite number of elements or be an infinite set. Two sets are equal if they have precisely the same elements.^{ [6]}
Sets are ubiquitous in modern mathematics. Indeed, set theory, more specifically Zermelo–Fraenkel set theory, has been the standard way to provide rigorous foundations for all branches of mathematics since the first half of the 20th century.^{ [5]}
History
The concept of a set emerged in mathematics at the end of the 19th century.^{ [7]} The German word for set, Menge, was coined by Bernard Bolzano in his work Paradoxes of the Infinite.^{ [8]}^{ [9]}^{ [10]}
Georg Cantor, one of the founders of set theory, gave the following definition at the beginning of his Beiträge zur Begründung der transfiniten Mengenlehre:^{ [1]}
A set is a gathering together into a whole of definite, distinct objects of our perception or our thought—which are called elements of the set.
Bertrand Russell called a set a class:^{ [11]}
When mathematicians deal with what they call a manifold, aggregate, Menge, ensemble, or some equivalent name, it is common, especially where the number of terms involved is finite, to regard the object in question (which is in fact a class) as defined by the enumeration of its terms, and as consisting possibly of a single term, which in that case is the class.
Naive set theory
The foremost property of a set is that it can have elements, also called members. Two sets are equal when they have the same elements. More precisely, sets A and B are equal if every element of A is an element of B, and every element of B is an element of A; this property is called the extensionality of sets.^{ [12]}
The simple concept of a set has proved enormously useful in mathematics, but paradoxes arise if no restrictions are placed on how sets can be constructed:
- Russell's paradox shows that the "set of all sets that do not contain themselves", i.e., {x | x is a set and x ∉ x}, cannot exist.
- Cantor's paradox shows that "the set of all sets" cannot exist.
Naïve set theory defines a set as any well-defined collection of distinct elements, but problems arise from the vagueness of the term well-defined.
Axiomatic set theory
In subsequent efforts to resolve these paradoxes since the time of the original formulation of naïve set theory, the properties of sets have been defined by axioms. Axiomatic set theory takes the concept of a set as a primitive notion.^{ [13]} The purpose of the axioms is to provide a basic framework from which to deduce the truth or falsity of particular mathematical propositions (statements) about sets, using first-order logic. According to Gödel's incompleteness theorems however, it is not possible to use first-order logic to prove any such particular axiomatic set theory is free from paradox.^{[ citation needed]}
How sets are defined and set notation
Mathematical texts commonly denote sets by capital letters^{ [14]}^{ [5]} in italic, such as A, B, C.^{ [15]} A set may also be called a collection or family, especially when its elements are themselves sets.
Roster notation
Roster or enumeration notation defines a set by listing its elements between curly brackets, separated by commas:^{ [16]}^{ [17]}^{ [18]}^{ [19]}
- A = {4, 2, 1, 3}
- B = {blue, white, red}.
In a set, all that matters is whether each element is in it or not, so the ordering of the elements in roster notation is irrelevant (in contrast, in a sequence, a tuple, or a permutation of a set, the ordering of the terms matters). For example, {2, 4, 6} and {4, 6, 4, 2} represent the same set.^{ [20]}^{ [15]}^{ [21]}
For sets with many elements, especially those following an implicit pattern, the list of members can be abbreviated using an ellipsis '...'.^{ [22]}^{ [23]} For instance, the set of the first thousand positive integers may be specified in roster notation as
- {1, 2, 3, ..., 1000}.
Infinite sets in roster notation
An infinite set is a set with an endless list of elements. To describe an infinite set in roster notation, an ellipsis is placed at the end of the list, or at both ends, to indicate that the list continues forever. For example, the set of nonnegative integers is
- {0, 1, 2, 3, 4, ...},
and the set of all integers is
- {..., −3, −2, −1, 0, 1, 2, 3, ...}.
Semantic definition
Another way to define a set is to use a rule to determine what the elements are:
- Let A be the set whose members are the first four positive integers.
- Let B be the set of colors of the French flag.
Such a definition is called a semantic description.^{ [24]}^{ [25]}
Set-builder notation
Set-builder notation specifies a set as a selection from a larger set, determined by a condition on the elements.^{ [25]}^{ [26]}^{ [27]} For example, a set F can be defined as follows:
- 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.^{ [28]}
Classifying methods of definition
Philosophy uses specific terms to classify types of definitions:
- An intensional definition uses a rule to determine membership. Semantic definitions and definitions using set-builder notation are examples.
- An extensional definition describes a set by listing all its elements.^{ [25]} Such definitions are also called enumerative.
- An ostensive definition is one that describes a set by giving examples of elements; a roster involving an ellipsis would be an example.
Membership
If B is a set and x is an element of B, this is written in shorthand as x ∈ B, which can also be read as "x belongs to B", or "x is in B".^{ [12]} The statement "y is not an element of B" is written as y ∉ B, which can also be read as "y is not in B".^{ [29]}^{ [30]}
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
The empty set (or null set) is the unique set that has no members. It is denoted ∅ or or { }^{ [31]}^{ [32]} or ϕ^{ [33]} (or ϕ).^{ [34]}
Singleton sets
A singleton set is a set with exactly one element; such a set may also be called a unit set.^{ [6]} Any such set can be written as {x}, where x is the element. The set {x} and the element x mean different things; Halmos^{ [35]} draws the analogy that a box containing a hat is not the same as the hat.
Subsets
If every element of set A is also in B, then A is described as being a subset of B, or contained in B, written A ⊆ B,^{ [36]} or B ⊇ A.^{ [37]} The latter notation may be read B contains A, B includes A, or B is a superset of A. 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.^{ [26]}
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),^{ [38]}^{ [29]} while others reserve A ⊂ B and B ⊃ A for cases where A is a proper subset of B.^{ [36]}
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,^{ [31]} and every set is a subset of itself:^{ [38]}
- ∅ ⊆ A.
- A ⊆ A.
Euler and Venn diagrams
An Euler diagram is a graphical representation of a collection of sets; each set is depicted as a planar region enclosed by a loop, with its elements inside. If A is a subset of B, then the region representing A is completely inside the region representing B. If two sets have no elements in common, the regions do not overlap.
A Venn diagram, in contrast, is a graphical representation of n sets in which the n loops divide the plane into 2^{n} zones such that for each way of selecting some of the n sets (possibly all or none), there is a zone for the elements that belong to all the selected sets and none of the others. For example, if the sets are A, B, and C, there should be a zone for the elements that are inside A and C and outside B (even if such elements do not exist).
Special sets of numbers in mathematics
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. ) or blackboard bold (e.g. ) typeface.^{ [39]} These include
- or , the set of all natural numbers: (often, authors exclude 0);^{ [39]}
- or , the set of all integers (whether positive, negative or zero): ;^{ [39]}
- or , the set of all rational numbers (that is, the set of all proper and improper fractions): . For example, −7/4 ∈ Q and 5 = 5/1 ∈ Q;^{ [39]}
- or , the set of all real numbers, including all rational numbers and all irrational numbers (which include algebraic numbers such as that cannot be rewritten as fractions, as well as transcendental numbers such as π and e);^{ [39]}
- or , the set of all complex numbers: C = {a + bi | a, b ∈ R}, for example, 1 + 2i ∈ C.^{ [39]}
Each of the above sets of numbers has an infinite number of elements. Each is a subset of the sets listed below it.
Sets of positive or negative numbers are sometimes denoted by superscript plus and minus signs, respectively. For example, represents the set of positive rational numbers.
Functions
A function (or mapping) from a set A to a set B is a rule that assigns to each "input" element of A an "output" that is an element of B; more formally, a function is a special kind of relation, one that relates each element of A to exactly one element of B. A function is called
- injective (or one-to-one) if it maps any two different elements of A to different elements of B,
- surjective (or onto) if for every element of B, there is at least one element of A that maps to it, and
- bijective (or a one-to-one correspondence) if the function is both injective and surjective — in this case, each element of A is paired with a unique element of B, and each element of B is paired with a unique element of A, so that there are no unpaired elements.
An injective function is called an injection, a surjective function is called a surjection, and a bijective function is called a bijection or one-to-one correspondence.
Cardinality
The cardinality of a set S, denoted |S|, is the number of members of S.^{ [40]} For example, if B = {blue, white, red}, then |B| = 3. Repeated members in roster notation are not counted,^{ [41]}^{ [42]} so |{blue, white, red, blue, white}| = 3, too.
More formally, two sets share the same cardinality if there exists a one-to-one correspondence between them.
The cardinality of the empty set is zero.^{ [43]}
Infinite sets and infinite cardinality
The list of elements of some sets is endless, or infinite. For example, the set of natural numbers is infinite.^{ [26]} In fact, all the special sets of numbers mentioned in the section above, are infinite. Infinite sets have infinite cardinality.
Some infinite cardinalities are greater than others. Arguably one of the most significant results from set theory is that the set of real numbers has greater cardinality than the set of natural numbers.^{ [44]} Sets with cardinality less than or equal to that of are called countable sets; these are either finite sets or countably infinite sets (sets of the same cardinality as ); some authors use "countable" to mean "countably infinite". Sets with cardinality strictly greater than that of are called uncountable sets.
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.^{ [45]}
The Continuum Hypothesis
The Continuum Hypothesis, formulated by Georg Cantor in 1878, is the statement that there is no set with cardinality strictly between the cardinality of the natural numbers and the cardinality of a straight line.^{ [46]} In 1963, Paul Cohen proved that the Continuum Hypothesis is independent of the axiom system ZFC consisting of Zermelo–Fraenkel set theory with the axiom of choice.^{ [47]} (ZFC is the most widely-studied version of axiomatic set theory.)
Power sets
The power set of a set S is the set of all subsets of S.^{ [26]} The empty set and S itself are elements of the power set of S, because these are both subsets of S. For example, the power set of {1, 2, 3} is {∅, {1}, {2}, {3}, {1, 2}, {1, 3}, {2, 3}, {1, 2, 3}}. The power set of a set S is commonly written as P(S) or 2^{S}.^{ [26]}^{ [48]}^{ [15]}
If S has n elements, then P(S) has 2^{n} elements.^{ [49]} For example, {1, 2, 3} has three elements, and its power set has 2^{3} = 8 elements, as shown above.
If S is infinite (whether countable or uncountable), then P(S) is uncountable. Moreover, the power set is always strictly "bigger" than the original set, in the sense that any attempt to pair up the elements of S with the elements of P(S) will leave some elements of P(S) unpaired. (There is never a bijection from S onto P(S).)^{ [50]}
Partitions
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.^{ [51]}^{ [52]}
Basic operations
There are several fundamental operations for constructing new sets from given sets.
Unions
Two sets can be joined: the union of A and B, denoted by A ∪ B, is the set of all things that are members of A or of B or of both.
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
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, 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.
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
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), 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 A^{c}.
- 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
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, 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
Sets are ubiquitous in modern mathematics. 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, x^{2}), 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) = x^{2}.
Principle of inclusion and exclusion
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
- ^
^{a}
^{b} Cantor, Georg; Jourdain, Philip E.B. (Translator) (1895).
"beiträge zur begründung der transfiniten Mengenlehre" [contributions to the founding of the theory of transfinite numbers]. Mathematische Annalen (in German). New York Dover Publications (1954 English translation). xlvi, xlix: 481–512, 207–246. Archived from
the original on 2011-06-10.
By an aggregate (Menge) we are to understand any collection into a whole (Zusammenfassung zu einem Gansen) M of definite and separate objects m (p.85)
- ^ P. K. Jain; Khalil Ahmad; Om P. Ahuja (1995). Functional Analysis. New Age International. p. 1. ISBN 978-81-224-0801-0.
- ^ Samuel Goldberg (1 January 1986). Probability: An Introduction. Courier Corporation. p. 2. ISBN 978-0-486-65252-8.
- ^ 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.
- ^ ^{a} ^{b} ^{c} Halmos 1960, p. 1.
- ^ ^{a} ^{b} Stoll, Robert (1974). Sets, Logic and Axiomatic Theories. W. H. Freeman and Company. pp. 5. ISBN 9780716704577.
- ^ 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.
- ^ Steve Russ (9 December 2004). The Mathematical Works of Bernard Bolzano. OUP Oxford. ISBN 978-0-19-151370-1.
- ^ 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.
- ^ Paul Rusnock; Jan Sebestík (25 April 2019). Bernard Bolzano: His Life and Work. OUP Oxford. p. 430. ISBN 978-0-19-255683-7.
- ^ Bertrand Russell (1903) The Principles of Mathematics, chapter VI: Classes
- ^ ^{a} ^{b} Halmos 1960, p. 2.
- ^ 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.
- ^ Seymor Lipschutz; Marc Lipson (22 June 1997). Schaum's Outline of Discrete Mathematics. McGraw Hill Professional. p. 1. ISBN 978-0-07-136841-4.
- ^ ^{a} ^{b} ^{c} "Introduction to Sets". www.mathsisfun.com. Retrieved 2020-08-19.
- ^ Charles Roberts (24 June 2009). Introduction to Mathematical Proofs: A Transition. CRC Press. p. 45. ISBN 978-1-4200-6956-3.
- ^ 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.
- ^ Ignacio Bello; Anton Kaul; Jack R. Britton (29 January 2013). Topics in Contemporary Mathematics. Cengage Learning. p. 47. ISBN 978-1-133-10742-2.
- ^ Susanna S. Epp (4 August 2010). Discrete Mathematics with Applications. Cengage Learning. p. 13. ISBN 978-0-495-39132-6.
- ^ Stephen B. Maurer; Anthony Ralston (21 January 2005). Discrete Algorithmic Mathematics. CRC Press. p. 11. ISBN 978-1-4398-6375-6.
- ^ 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.
- ^ Alfred Basta; Stephan DeLong; Nadine Basta (1 January 2013). Mathematics for Information Technology. Cengage Learning. p. 3. ISBN 978-1-285-60843-3.
- ^ Laura Bracken; Ed Miller (15 February 2013). Elementary Algebra. Cengage Learning. p. 36. ISBN 978-0-618-95134-5.
- ^ Halmos 1960, p. 4.
- ^ ^{a} ^{b} ^{c} 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.
- ^ ^{a} ^{b} ^{c} ^{d} ^{e} John F. Lucas (1990). Introduction to Abstract Mathematics. Rowman & Littlefield. p. 108. ISBN 978-0-912675-73-2.
- ^ Weisstein, Eric W. "Set". mathworld.wolfram.com. Retrieved 2020-08-19.
- ^ Ralph C. Steinlage (1987). College Algebra. West Publishing Company. ISBN 978-0-314-29531-6.
- ^ ^{a} ^{b} Marek Capinski; Peter E. Kopp (2004). Measure, Integral and Probability. Springer Science & Business Media. p. 2. ISBN 978-1-85233-781-0.
- ^ "Set Symbols". www.mathsisfun.com. Retrieved 2020-08-19.
- ^ ^{a} ^{b} Halmos 1960, p. 8.
- ^ 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.
- ^ Aggarwal, M.L. (2021). "1. Sets". Understanding ISC Mathematics Class XI. Vol. 1. Arya Publications (Avichal Publishing Company). p. A=3.
- ^ Sourendra Nath, De (January 2015). "Unit-1 Sets and Functions: 1. Set Theory". Chhaya Ganit (Ekadash Shreni). Scholar Books Pvt. Ltd. p. 5.
- ^ Halmos 1960, Sect.2.
- ^ ^{a} ^{b} Felix Hausdorff (2005). Set Theory. American Mathematical Soc. p. 30. ISBN 978-0-8218-3835-8.
- ^ 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.
- ^ ^{a} ^{b} Halmos 1960, p. 3.
- ^ ^{a} ^{b} ^{c} ^{d} ^{e} ^{f} 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.
- ^ Yiannis N. Moschovakis (1994). Notes on Set Theory. Springer Science & Business Media. ISBN 978-3-540-94180-4.
- ^ Arthur Charles Fleck (2001). Formal Models of Computation: The Ultimate Limits of Computing. World Scientific. p. 3. ISBN 978-981-02-4500-9.
- ^ William Johnston (25 September 2015). The Lebesgue Integral for Undergraduates. The Mathematical Association of America. p. 7. ISBN 978-1-939512-07-9.
- ^ Karl J. Smith (7 January 2008). Mathematics: Its Power and Utility. Cengage Learning. p. 401. ISBN 978-0-495-38913-2.
- ^ 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.
- ^ David Tall (11 April 2006). Advanced Mathematical Thinking. Springer Science & Business Media. p. 211. ISBN 978-0-306-47203-9.
- ^ Cantor, Georg (1878). "Ein Beitrag zur Mannigfaltigkeitslehre". Journal für die Reine und Angewandte Mathematik. 1878 (84): 242–258. doi: 10.1515/crll.1878.84.242.
- ^ Cohen, Paul J. (December 15, 1963). "The Independence of the Continuum Hypothesis". Proceedings of the National Academy of Sciences of the United States of America. 50 (6): 1143–1148. Bibcode: 1963PNAS...50.1143C. doi: 10.1073/pnas.50.6.1143. JSTOR 71858. PMC 221287. PMID 16578557.
- ^ Halmos 1960, p. 19.
- ^ Halmos 1960, p. 20.
- ^ 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.
- ^ Toufik Mansour (27 July 2012). Combinatorics of Set Partitions. CRC Press. ISBN 978-1-4398-6333-6.
- ^ Halmos 1960, p. 28.
References
- Dauben, Joseph W. (1979). Georg Cantor: His Mathematics and Philosophy of the Infinite. Boston: Harvard University Press. ISBN 0-691-02447-2.
- Halmos, Paul R. (1960). Naive Set Theory. Princeton, N.J.: Van Nostrand. ISBN 0-387-90092-6.
- Stoll, Robert R. (1979). Set Theory and Logic. Mineola, N.Y.: Dover Publications. ISBN 0-486-63829-4.
- Velleman, Daniel (2006). How To Prove It: A Structured Approach. Cambridge University Press. ISBN 0-521-67599-5.
External links
- The dictionary definition of set at Wiktionary
- Cantor's "Beiträge zur Begründung der transfiniten Mengenlehre" (in German)