1. Introduction to Set Theory
A set is a structure, representing an unordered collection (group, plurality) of zero or more distinct (different) objects.
Set theory deals with operations between, relations among, and statements about sets.

2. Basic notations for sets
Discrete Mathematics and its Applications
Basic notations for sets
For sets, we’ll use variables S, T, U, …
We can denote a set S in writing by listing all of its elements in curly braces:
{a, b, c} is the set of whatever 3 objects are denoted by a, b, c.
Set builder notation: For any proposition P(x) over any universe of discourse, {x|P(x)} is the set of all x such that P(x).
e.g., {x | x is an integer where x>0 and x<5 }
Read {a, b, c} as “the set whose elements are a, b, and c” or just “the set a, b, c”.
(c) , Michael P. Frank

3. Basic properties of sets
Sets are inherently unordered:
No matter what objects a, b, and c denote, {a, b, c} = {a, c, b} = {b, a, c} = {b, c, a} = {c, a, b} = {c, b, a}.
All elements are distinct (unequal); multiple listings make no difference!
{a, b, c} = {a, a, b, a, b, c, c, c, c}.
This set contains at most 3 elements!

4. Definition of Set Equality
Two sets are declared to be equal if and only if they contain exactly the same elements.
In particular, it does not matter how the set is defined or denoted.
For example: The set {1, 2, 3, 4} = {x | x is an integer where x>0 and x<5 } = {x | x is a positive integer whose square is >0 and <25}

5. Infinite Sets
Conceptually, sets may be infinite (i.e., not finite, without end, unending).
Symbols for some special infinite sets: N = {0, 1, 2, …} The natural numbers. Z = {…, -2, -1, 0, 1, 2, …} The integers. R = The “real” numbers, such as …
Infinite sets come in different sizes!

6. Discrete Mathematics and its Applications
Venn Diagrams 2 4 6 8 -1 1
Even integers from 2 to 9 3 5
With Venn diagrams, you can see that one set is a subset of another just by seeing that you can draw an enclosure around its members that fits completely inside an enclosure drawn around the larger set’s members. 7 9
Odd integers from 1 to 9
Positive integers less than 10
Primes <10
Integers from -1 to 9
(c) , Michael P. Frank

7. Basic Set Relations: Member of
xS (“x is in S”) is the proposition that object x is an lement or member of set S.
e.g. 3N, “a”{x | x is a letter of the alphabet}
Can define set equality in terms of  relation: S,T: S=T  (x: xS  xT) “Two sets are equal iff they have all the same members.”
xS : (xS) “x is not in S”

8. The Empty Set
 (“null”, “the empty set”) is the unique set that contains no elements whatsoever.
 = {} = {x|False}
No matter the domain of discourse, we have the axiom
x: x.

9. Subset and Superset Relations
Discrete Mathematics and its Applications
Subset and Superset Relations
ST (“S is a subset of T”) means that every element of S is also an element of T.
ST  x (xS  xT)
S, SS.
ST (“S is a superset of T”) means TS.
Note S=T  ST ST.
means (ST), i.e. x(xS  xT)
Note also that FORALL x P(x)->Q(x) can also be understood as meaning “{x|P(x)} is a subset of {x|Q{x}}”. This can help you understand the meaning of implication. For example, if I say, “if a student has a drivers license, then he is over 16,” this is the same as saying “the set of students with drivers licenses is a subset of the set of students who are over 16”, or “every student with a drivers license is over 16.” If no students in the universe of discourse have drivers licenses, then the antecedent is always false, or in other words the set of students with drivers licenses is just the empty set, which is of course a member of every set, and so the statement is vacuously true. Alternatively, if every student in the universe of discourse is over 16, then the consequent is always true, that is, the set of students who are over 16 is the entire universe of discourse, and so every set of students in the u.d. is necessarily a subset of the set of students who are over 16, and so the statement is trivially true. The statement is only false if there exists a student with a drivers license in the u.d. who is under 16 (perhaps the license is fake or from a foreign country), in which case, the set of students with drivers licenses is *not* a subset of the under-16 students.
(c) , Michael P. Frank

10. Proper (Strict) Subsets & Supersets
Discrete Mathematics and its Applications
Proper (Strict) Subsets & Supersets
ST (“S is a proper subset of T”) means that ST but Similar for ST.
Example: {1,2}  {1,2,3}
We may also say, “S is a strict subset of T”, or “S is strictly a subset of T” to mean the same thing. S T
Venn Diagram equivalent of ST
(c) , Michael P. Frank

11. Discrete Mathematics and its Applications
Sets Are Objects, Too!
The objects that are elements of a set may themselves be sets.
E.g. let S={x | x  {1,2,3}} then S={, {1}, {2}, {3}, {1,2}, {1,3}, {2,3}, {1,2,3}}
Note that 1  {1}  {{1}} !!!!
In general, any kind of object or structure, whether simple or complex, can be a member of a set. In particular, sets themselves (being structures) can be members of sets.
If you don’t understand the distinction between 1, {1}, {{1}}, you’ll make endless silly mistakes. 1 is a number, the number one. {1} is NOT A NUMBER AT ALL! It is a COMPLETELY DIFFERENT TYPE OF OBJECT! Namely, it is a set. What kind of set? It is a singleton set, by which we mean a set that contains exactly one element. In this case, its element happens to be the number 1. Now, what is {{1}}? It is also a set, and also a singleton set, but it is a COMPLETELY DIFFERENT TYPE of singleton set. To see this, notice that {1} is a set of numbers, whereas {{1}} is not a set of numbers at all! It is a SET OF SETS. Its single element is not a number at all, but is a SET. Namely, the set {1}. In other words, {{1}} is the singleton set whose member is the singleton set whose member is 1. Whereas, {1} is just the singleton set whose member is 1. And, 1 is just 1. All of these are distinct objects and you’ve got to learn to keep them separate! Otherwise, you’ll never have a chance of understanding data types in programming languages. For example, in most languages, we can have an array of numbers, or an array of arrays of numbers, etc. These are all completely different types of objects and can never be compatible with each other.
Very
Important!
(c) , Michael P. Frank

12. Cardinality and Finiteness
|S| (read “the cardinality of S”) is a measure of how many different elements S has.
E.g., ||=0, |{1,2,3}| = 3, |{a,b}| = 2, |{{1,2,3},{4,5}}| = ____
We say S is infinite if it is not finite.
What are some infinite sets we’ve seen? 2 N Z R

13. Cardinality and Finiteness
“The number of elements in a set.”
Let A be a set.
If A =  (the empty set), then the cardinality of A is 0.
b. If A has exactly n elements, n a natural number, then the cardinality of A is n. The set A is a finite set.
c. Otherwise, A is an infinite set.

14. Notation The cardinality of a set A is denoted by | A |.
If A =  , then | A |= 0.
If A has exactly n elements, then | A | = n.
c. If A is an infinite set, then | A | = .

15. Examples:
A = {2, 3, 5, 7, 11, 13, 17, 19}; | A | = 8
A = N (natural numbers); | N | = 
A = Q (rational numbers); | Q | = 
A = {2n | n is an integer}; | A | = 
(the set of even integers)

16. DEFINITION Let A and B be sets. Then,
|A| = |B| if and only if there is a one-to-one correspondence between the elements of A and the elements of B.
Examples:
1. A = {1, 2, 3, 4, 5}
B = {a, e, i, o, u}
1 a, 2 e, 3 i, 4 o, 5 u; |B| = 5

17. DEFINITION 2. A = N (the natural numbers)
B = {2n | n is a natural number} (the even natural numbers)
n 2n is a one-to one correspondence between A and B. Therefore, |A| = |B|; |B| = .
3. A = N (the natural numbers)
C = {2n 1 | n is a natural number} (the odd natural numbers)
n 2n 1 is a one-to one correspondence between A and C. Therefore, |A| = |C|; |C| = .

18. Countable Sets DEFINITIONS:
1. A set S is finite if there is a one-to-one correspondence between it and the set
{1, 2, 3, . . ., n} for some natural number n.
2. A set S is countably infinite if there is a one-to-one correspondence between it and the natural numbers N.

19. Countable Sets DEFINITIONS:
A set S is countable if it is either finite or countably infinite.
A set S is uncountable if it is not countable.

20. Examples:
1. A = {1, 2, 3, 4, 5, 6, 7},
 = {a, b, c, d, x, y, z}
are finite sets; |A| = 7, | | = 26 .
N (the natural numbers), Z (the integers), and Q (the rational numbers) are countably infnite sets;
that is, |Q| = |Z| = |N|.

21. Examples: 3. I (the irrational numbers) and 
 (the real numbers) are uncountable sets;
that is
|I| > |N| and | | > |N|.

22. Some Facts:
A set S is finite if and only if for any proper subset A  S, |A| < |S|; that is, “proper subsets of a finite set have fewer elements.”
Suppose that A and B are infinite sets and A  B. If B is countably infinite then A is countably infinite and |A| = |B|.

23. Some Facts: 3. Every subset of a countable set is countable.
If A and B are countable sets, then A  B is a countable set.

24. Irrational Numbers, Real Numbers
Irrational numbers: “points on the real line
that are not rational points”; decimals that
are neither repeating nor terminating.
Real numbers: “rationals”  “irrationals”

25. is a real number:

26. is not a rational number, i.e., is an irrational number.
Proof:
Suppose is a rational number. Then
. . .

27. Other examples of irrational numbers:
Square roots of rational numbers that are not
perfect squares.
Cube roots of rational numbers that are not
perfect cubes.
And so on.
  , e 

28. Algebraic numbers –
roots of polynomials with integer coefficients.
Transcendental numbers –
irrational numbers that are not algebraic.

29. THEOREM: The real numbers are uncountable!
Proof: Consider the real numbers on the
interval [0,1]. Suppose they are countable.
Then . . .
Arrive at a contradiction.
COROLLARY: The irrational numbers
are uncountable.
Proof: Real numbers: “rationals”  “irrationals”

30. The Power Set Operation
Discrete Mathematics and its Applications
The Power Set Operation
The power set P(S) of a set S is the set of all subsets of S. P(S) = {x | xS}.
E.g. P({a,b}) = {, {a}, {b}, {a,b}}.
Sometimes P(S) is written 2S. Note that for finite S, |P(S)| = 2|S|.
It turns out that |P(N)| > |N|. There are different sizes of infinite sets!
We’ll get to different sizes of infinite sets later, in the module on functions.
(c) , Michael P. Frank

31. Discrete Mathematics and its Applications
Ordered n-tuples
For nN, an ordered n-tuple or a sequence of length n is written (a1, a2, …, an). The first element is a1, etc.
These are like sets, except that duplicates matter, and the order makes a difference.
Note (1, 2)  (2, 1)  (2, 1, 1).
Empty sequence, singlets, pairs, triples, quadruples, quintuples, …, n-tuples.
Sometimes people also define “bags”, which are unordered collections in which duplicates matter. If you have a bag of coins, they are in no particular order, but it matters how many coins of each type you have.
(c) , Michael P. Frank

32. Cartesian Products of Sets
Discrete Mathematics and its Applications
Cartesian Products of Sets
For sets A, B, their Cartesian product AB : {(a, b) | aA  bB }.
E.g. {a,b}{1,2} = {(a,1),(a,2),(b,1),(b,2)}
Note that for finite A, B, |AB|=|A||B|.
Note that the Cartesian product is not commutative: AB: AB =BA.
Extends to A1  A2  …  An...
Usually AxBxC is defined as {(a,b,c) | a is in A and b is in B and c is in C}.
(c) , Michael P. Frank

33. The Union Operator
For sets A, B, their union AB is the set containing all elements that are either in A, or (“”) in B (or, of course, in both).
Formally, A,B: AB = {x | xA  xB}.
Note that AB contains all the elements of A and it contains all the elements of B: A, B: (AB  A)  (AB  B)

34. Union Examples Required Form 2 5 3 7 {a,b,c}{2,3} = {a,b,c,2,3}
{2,3,5}{3,5,7} = {2,3,5,3,5,7} ={2,3,5,7}
Required Form 2 3 5 7

35. The Intersection Operator
For sets A, B, their intersection AB is the set containing all elements that are simultaneously in A and (“”) in B.
Formally, A,B: AB{x | xA  xB}.
Note that AB is a subset of A and it is a subset of B: A, B: (AB  A)  (AB  B)

36. Intersection Examples
{a,b,c}{2,3} = ___
{2,4,6}{3,4,5} = ______ 
{4} 2 3 5 6 4

37. Help, I’ve been disjointed!
Disjointedness
Help, I’ve been disjointed!
Two sets A, B are called disjoint (i.e., unjoined) iff their intersection is empty. (AB=)
Example: the set of even integers is disjoint with the set of odd integers.

38. Inclusion-Exclusion Principle
Discrete Mathematics and its Applications
Inclusion-Exclusion Principle
How many elements are in AB? |AB| = |A|  |B|  |AB|
Example:
{2,3,5}{3,5,7} = {2,3,5,3,5,7} ={2,3,5,7}
Subtract out items
in intersection, to
compensate for
double-counting them!
We will see this basic counting principle again when we talk about combinatorics.
(c) , Michael P. Frank

39. Discrete Mathematics and its Applications
Set Difference
For sets A, B, the difference of A and B, written AB, is the set of all elements that are in A but not B.
A  B : x  xA  xB  x   xA  xB  
Also called: The complement of B with respect to A.
NOT (x in A -> x in B) = NOT (x not in A or x in B) (defn. of implies) = x in A AND x not in B (DeMorgan’s law).
(c) , Michael P. Frank

40. Set Difference Examples
{1,2,3,4,5,6}  {2,3,5,7,9,11} = ___________
Z  N  {… , -1, 0, 1, 2, … }  {0, 1, … } = {x | x is an integer but not a nat. #} = {x | x is a negative integer} = {… , -3, -2, -1}
{1,4,6}

41. Set Difference - Venn Diagram
A-B is what’s left after B “takes a bite out of A”
Chomp!
Set AB
Set A
Set B

42. Set Complements
The universe of discourse can itself be considered a set, call it U.
The complement of A, written , is the complement of A w.r.t. U, i.e., it is UA.
E.g., If U=N,

43. More on Set Complements
Discrete Mathematics and its Applications
More on Set Complements
An equivalent definition, when U is clear:
Note that set difference and complement do not relate to each other like arithmetic difference and negative. In arithmetic, we know that a-b = -(b-a). But in sets, A-B is not generally the same as the complement of B-A. A U
(c) , Michael P. Frank

44. Set Identities Identity: A=A AU=A Domination: AU=U A=
Idempotent: AA = A = AA
Double complement:
Commutative: AB=BA AB=BA
Associative: A(BC)=(AB)C A(BC)=(AB)C

45. DeMorgan’s Law for Sets
Exactly analogous to (and derivable from) DeMorgan’s Law for propositions.

46. Proving Set Identities
Discrete Mathematics and its Applications
Proving Set Identities
To prove statements about sets, of the form E1 = E2 (where Es are set expressions), here are three useful techniques:
Prove E1  E2 and E2  E1 separately.
Use logical equivalences.
Use a membership table.
A membership table is like a truth table.
(c) , Michael P. Frank

47. Method 1: Mutual subsets
Example: Show A(BC)=(AB)(AC).
Show A(BC)(AB)(AC).
Assume xA(BC), & show x(AB)(AC).
We know that xA, and either xB or xC.
Case 1: xB. Then xAB, so x(AB)(AC).
Case 2: xC. Then xAC , so x(AB)(AC).
Therefore, x(AB)(AC).
Therefore, A(BC)(AB)(AC).
Show (AB)(AC)  A(BC). …

48. Method 3: Membership Tables
Just like truth tables for propositional logic.
Columns for different set expressions.
Rows for all combinations of memberships in constituent sets.
Use “1” to indicate membership in the derived set, “0” for non-membership.
Prove equivalence with identical columns.

49. Membership Table Example
Prove (AB)B = AB.

50. Membership Table Exercise
Prove (AB)C = (AC)(BC).

51. Generalized Union Binary union operator: AB
n-ary union: AA2…An : ((…((A1 A2) …) An) (grouping & order is irrelevant)
“Big U” notation:
Or for infinite sets of sets:

52. Generalized Intersection
Binary intersection operator: AB
n-ary intersection: AA2…An((…((A1A2)…)An) (grouping & order is irrelevant)
“Big Arch” notation:
Or for infinite sets of sets:

53. Multisets
A multiset is a set of elements, each of which has a multiplicity
The size of the multiset is the sum of the multiplicities of all the elements
Example:
{X, Y, Z} with m(X)=0 m(Y)=3, m(Z)=2
Unary visualization: {Y, Y, Y, Z, Z}

54. Counting Multisets n + k - 1 n + k - 1 = k n - 1 The number of ways
to choose a multiset of
size k from n types of elements is:
n + k - 1
n - 1
n + k - 1 k =

55. Example : Pirates
How many ways are there of choosing 20 pirates from a set of 5 pirates, with repetitions allowed? 20 24 20 24 4 = =

56. Operations on multiset : Union
For multisets A, B, their union AB is the multiset containing maximum of the multiplicities of the elements in A and in B.
Example: A = { a, a, a, c, d, d} B = {a, a, b, c, c}
AB = {a, a, a, b, c, c, d, d}

57. Operations on multiset : intersection
For multisets A, B, their intersection A  B is the multiset such that multiplicity of an element is equal to minimum of the multiplicities of the elements in A and B
Example : A = { a, a, a, c, d, d} B = {a, a, b, c, c}
A  B = {a, a, c}

58. Operations on multiset : difference
For multisets A, B, their difference A - B is the multiset such that multiplicity of an element is equal to multiplicity of an element in A minus multiplicity of an element in B
Example : A = { a, a, a, b, b, c, d, d, e} B = {a, a, b, b, b, c, c, d, d, f}
A - B = {a, e}

59. Operations on multiset : sum
For multisets A, B, their intersection A + B is the multiset such that multiplicity of an element is equal to sum of multiplicities of the elements in A and B
Example : A = { a, a, b, c, c} B = {a, b, b, d}
A  B = {a, a, a, b, b, b, c, c, d}