# Definition 14 A set is an unordered collection of elements or objects.

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1 Chapter 4 Set Theory Definition 14 A set is an unordered collection of elements or objects. Primitive Notation EXAMPLE {1, 2, 3} is a set containing 3 elements: 1, 2, and 3. EXAMPLE {1, 2, 3} = {3, 2, 1} (order irrelevant). EXAMPLE {1, 1, 3, 2, 2} = {1, 2, 3} (number of occurrences irrelevant). EXAMPLE {0, 1, 2,...} is the set of natural numbers N (infinite set). EXAMPLE = {} (empty set contains no elements). EXAMPLE { } = {{}}. Definition 15 We denote x is an element of the set S byx S. x is not an element of the set S byx S. every element of the set A is also an element of the set B bya B, i.e. ( x)x A x B. The Venn diagram for A B 35

2 36 CHAPTER 4. SET THEORY Definition 16 A is a superset of B, denoteda B if and only if B A. Definition 17 A = B if and only if A and B have exactly the same elements. By the definition of equality of the sets A and B: A = B iff x(x A x B) iff A B and A B iff A B and B A If you show only one of these, you re half done! Note. Showing two sets begin equal involves showing the following 2 things: 1. x(x A x B), which gives us A B, and 2. x(x B x A), which gives us B A. 4.1 Proper Subset Also written A B by some authors, although this is misguided because other (really misguided) authors use A B to mean A B. Definition 18 A is a proper subset of B, denoteda B, if A B but not B A, i.e.a B but A B. A is a proper subset of B iff: x(x A x B) x(x B x A) x(x A x B) x ( (x B) x A) x(x A x B) x(x B (x A)) x(x A x B) x(x A x B).

3 4.2. WAYS TO DEFINE SETS 37 EXAMPLE {1, 2, 3} {1, 2, 3, 5} {1, 2, 3} {1, 2, 3, 5} Question: Is {1, 2, 3}? Answer: Yes: x[(x ) (x {1, 2, 3})] Since x is false, the implication is true. Fact 6 is a subset of every set. is a proper subset of every set except. EXAMPLE Is {1, 2, 3}? EXAMPLE Is {, 1, 2, 3}? EXAMPLE Is {, 1, 2, 3}? No. Yes. Yes. 4.2 Ways to Define Sets 1. List the elements explcitly (works only for finite sets). EXAMPLE {John,Paul,George,Ringo} 2. List them implicitly. EXAMPLE {1, 2, 3,...} EXAMPLE {2, 3, 5, 7, 11, 13, 17, 19, 23,...} 3. Describe a property that defines the set ( set builder notation). EXAMPLE {x : x is prime } EXAMPLE {x x is prime } EXAMPLE {x : P (x) is true. } (where P is a predicate). Let D(x, y) be the predicate x is divisible by y. Then this set becomes D(x, y) k(k.y = x). {x : y[(y >1) (y <x)] D(x, y)}

4 38 CHAPTER 4. SET THEORY Question: Can we use any predicate P to define a set S = {x : P (x)} Russell s Paradox Let Is S S? S = {x : x is a set such that x x}. If S S then by the definition of S, S S. If S S then by the definition of S, S S. EXAMPLE There is a town with a barber who shaves all and only the people who don t shave themselves. Question: Who shaves the barber? 4.3 Cardinality of a Set Definition 19 IF S is finite, then the cardinality of S (written S ) is the number of (distinct) elements in S. EXAMPLE S= {1, 2, 5, 6} has cardinality S =4. EXAMPLE S= {1, 1, 1, 1, 1} has cardinality S =1. EXAMPLE =0. EXAMPLE S= {, { }, {, { }}} has cardinality S =3. We will discuss infinite cardinality later. EXAMPLE The cardinality of N = {0, 1, 2, 3,...} is infinite. 4.4 Power Set In other words, the power set of S is the set of all subsets of S Definition 20 If S is a set, then the power set of S, written 2 S or P(S) or P (S) is defined by: 2 S = {x : x S} EXAMPLE S= {a} has the power set 2 S = {, {a}}. EXAMPLE S= {a, b} has the power set 2 S = {, {a}, {b}, {a, b}}.

5 4.5. CARTESIAN PRODUCT 39 EXAMPLE S= has the power set 2 S = { }. EXAMPLE S= { } has the power set 2 S = {, { }}. EXAMPLE S= {, { }} has the power set 2 S = {, { }, {{ }}, {, { }}}. Fact 7 If S is finite, then 2 S =2 S. Question. set of Who cares if {, {, { }}, { }} is a subset of the power {{ },, {, { }, {, { }}}}? Answer. No body! Question. Then why ask the question? Answer. We must learn to pick nits. 4.5 Cartesian Product Definition 21 The Cartesian product of two sets A and B is the set A B = { a, b : a A b B} of ordered pairs. Similarly, the Cartesian product of n sets A 1,...,A n is the set A 1 A n = { a 1,...,a n : a 1 A 1... a n A n } of ordered n-tuples. EXAMPLE If A = {john, mary, fred} and B = {doe, rowe}, then A B = { john, doe, mary, doe, fred, doe, john, roe, mary, roe, fred, roe } Fact 8 If A and B be finite, then A B = A. B. 4.6 Set Operations Union of Two Sets Definition 22 For sets A and B, theunion of A and B is the set A B = {x : x A x B}.

6 40 CHAPTER 4. SET THEORY Intersection of Two Sets Definition 23 For sets A and B, theintersection of A and B is the set A B = {x : x A x B}. EXAMPLE {presidents} {deceased} = {deceased presidents} EXAMPLE {US presidents} {people in this room} = Note. If for sets A and B, A B =, A and B are said to be disjoint Complement of a Set Definition 24 Assume U be the universe of discourse (U contains all elements under consideration). Then the complement of a set A is the set A = {x U : x A} which is the same as the set {x : x U x A} or {x : x A} when U is understood implicitly.

7 4.6. SET OPERATIONS 41 Note. = U and U =. EXAMPLE IF U = {1, 2, 3} and A = {1} then A = {2, 3} Set Difference of two Sets Definition 25 For sets A and B the set difference of A from B is defined as the set A B = {x : x A x B} = A B. EXAMPLE {people in class} {sleeping people} = {awake people in class}. EXAMPLE {US presidents} {baboons} = {US presidents}.? Note. A A = A Symmeteric Difference (Exclusive-Or) of two Sets Definition 26 For sets A and B, thesymmetricdifferenceofa and B is the set A B = {x :(x A x B) (x A x B}. From the definition: A B = {x :(x A x B) (x A x B} = {x :(x A B) (x B A)} = {x : x (A B) (B A)} = (A B) (B A).

8 42 CHAPTER 4. SET THEORY 4.7 Famous Set Identities Identity A U = A A = A Domination A U = U A = Idempotent A A = A A A = A Double Negation (A)) = A Commutative A B = B A A B = B A Associative (A B) r = A (B r) (A B) r = A (B r) Excluded Middle Uniqueness A A = U A A = Distributive A (B r) = (A B) (A r) A (B r) = (A B) (A r) De Morgan s (A B) = A B De Morgan s (A B) = A B Don t memorize these; understand them!

9 WAYS TO PROVE IDENTITIES Ways to Prove Identities To show that two sets A and B are equal we can use one of the following four techniques. 1. Show that A B and B A. EXAMPLE We show that A B = A B (first proof). ( ) If x A B, thenx A B. So,x A and x B, andthusx A B. ( ) If x A B then x A and x B. So,x A B and therefor x A B. 2. Use a membership table. Works the same way as a truth table in which we use 0s and 1s to indicate the followings. 0: x is not in the specified set. 1: x is in the specified set. EXAMPLE We show that A B = A B (second proof). A B A B A B A B A B Use previous identities. EXAMPLE We show that A B = A B (third proof). (A B) (A) (B) by double complement (A) (B) by De Morgan s law 2 (A) (B) by double complement A B 4. Use logical equivalences of the defining propositions. EXAMPLE We show that A B = A B (fourth proof).

10 44 CHAPTER 4. SET THEORY A B = {x : (x A x B)} = {x :( x A) ( x B)} = {x :(x A) (x B)} = {x :(x A B)} = A B 4.9 Generalized Union and Intersection Definition 27 n A i = A 1 A 2... A n i=1 = {x : x A 1 x A 2...x A n } n A i = A 1 A 2... A n i=1 = {x : x A 1 x A 2...x A n } 4.10 Representation of Sets as Bit Strings Definition 28 Let U = {x 1,x 2,...,x n } be the universe and A be some set in this universe. Then we can represent A by a sequence of bits (0s and 1s) of length n in which the i-th bit is 1 if x i A and 0 otherwise. We call this string the characteristic vector of A. EXAMPLE If U = {x 1,x 2,x 3,x 4,x 5 } and A = {x 1,x 2,x 4 },thenthecharacteristic vector of A will be Fact 9 To find the characteristic vector for A B we take the bitwise or of the characteristic vectors of A and B. To find the characteristic vector for A B we take the bitwise and of the characteristic vectors of A and B. EXAMPLE If U = {x 1,x 2,x 3,x 4,x 5 } and A = {x 1,x 2,x 4 } and B = {x 1,x 3,x 4,x 5 }, then the characteristic vector of A will be and the characteristic vector of B will be Then for the characteristic vector of A B and A B we have get.

11 4.11. PRINCIPLE OF INCLUSION/EXCLUSION 45 A : B : A B A B Principle of Inclusion/Exclusion We start with an example. EXAMPLE How many people wear hats or gloves? Number of people wearing hats or gloves = Number of people wearing hats + Number of people wearing gloves Number of people wearing both hats and gloves. In general it is easy to see that A B = A + B A B. EXAMPLE If we have 217 CS majors, 157 taking CS 125, 145 taking CS 173, and 98 taking both, how many are not taking either? Answer: The number of people who are not taking either is 217 minus the number of people who are taking CS 125 or CS 173 which is 217 ( ) = = General Inclusion/Exclusion It can be checked easily when we have three sets A, B, andc that A B C = A + B + C A B A C B C + A B C This can be generalized as follows. Fact 10 For sets A 1,A 2,...,A n the inclusion/exclusion principle is stated as follows: A 1 A 2... A n = A i A i A j + A i A j A k 1 i n 1 i<j n 1 i<j<k n + +( 1) n A 1 A 2... A n 4.13 Functions Definition 29 A function f : A B is a subset of A B such that a A!b B a, b f.

12 46 CHAPTER 4. SET THEORY From the above definition we cannot have a, b f, and a, c f for b c. Also there must be for each a, someb such that a, b f. Didn t say that b!a a, b f. Note. There can be a, b f and c, b f. We write f(a) =b to indicate that b is the unique element of B such that a, b f. though this intuition fails... more later. Intuitively we can think of f as a rule, assigning to each a A a b B. EXAMPLE A= {Latoya, Germaine, Michael, Teddy, John F., Robert} B = {Mrs Jackson, Rose Kennedy, Mother Theresa} f : A B,f(a) =mother(a) f is a function because everyone has exactly one (biological) mother. Mrs Jackson has more than 1 child. Functions do not require b B!a A f(a) =b. Mother Theresa (paradoxically) is not a mother. Functions do not require b B a A f(a) =b. Definition 30 For a function f : A B, A is called the domain of f and B is called the co-domain of f. For a set S A the image of A is defined as image(a) ={f(a) :a S} Note. When I was a lad we used range instead of co-domain. Now range is used sometimes as co-domain and sometimes as image. EXAMPLE In the previous example: image({latoya, Michael, John}) ={Mrs Jackson, Rose Kennedy} and image({latoya, Michael}) ={Mrs Jackson}.

13 4.13. FUNCTIONS 47 Note. image(s) ={f(a) :a S} = {b B : a A f(a) =b} Definition 31 The range of a function f : A B is image(a). a A is a pre-image of b B if f(a) =b. ForasetS B, the pre-image of S is defined as pre-image(s) ={pre-image(b) : b B} The above concepts are represented pictorially below. Suppose f : A B is a function. image(a) =f(a) pre-image(b) image(s) pre-image(s)

14 48 CHAPTER 4. SET THEORY Questions. What is the relationship between these two? image(pre-image(s)) and pre-image(image(s)) Definition 32 A function f is one-to-one, or injective, or is an injection, if a, b, c (f(a) =b f(c) =b) a = c. In other words each b B has at most one pre-image. EXAMPLE The functions f(x) =mother(x) in the previous example was not one-to-one because f(latoya) = f(michael) = Mrs Jackson. EXAMPLE f: R + R +,wheref(x) =x 2 is one-to-one, since each positive real x has exactly one positive pre-image ( x). EXAMPLE f: R R, wheref(x) =x 2 is not one-to-one. f(2) = 4 = f( 2). Note. In terms of diagrams, one-to-one means that no more than one arrow go to the same point in B. Definition 33 Afunctionf : A B is onto, orsurjective, oris a surjection if b B a A f(a) =b In other words, everything in B has at least one pre-image. EXAMPLE In the mothers example, the function f(x) =mother(x) is not surjective because Mother Theresa is not the mother of anyone in A. EXAMPLE f: R R, wheref(x) =x 2 is not surjective, since 1 hasno squared roots in R. In fact 2 squared roots. EXAMPLE f: R R +,wheref(x) =x 2 is surjective, since every positive number has at least one squared root Bijections Definition 34 Afunctionf : A B is a bijection, oraone-to-onecorrespondence, if and only if f is one-to-one and onto (injective and surjective). In other words, f : A B is a bijection iff: every b B has exactly one pre-image, and

15 4.15. CARDINALITY OF INFINITE SETS 49 always true by the definiafunctions. every a A has exactly one image. Definition 35 The inverse function of a bijection f, denotedbyf 1 is the function f 1 : B A where f 1 (b) is defined as the unique a such that f(a) =b Cardinality of Infinite Sets Motivating Questions: Are there more even numbers, or odd numbers? Are there more natural numbers than evens? Are there more evens than numbers divisible by 3? The answer to the above questions depends on what we mean by more then. Definition 36 Two sets A and B have the same cardinality if and only if there exists a bijection between A and B (written A B). A set is countably infinite if it can be put into one-to-one correspondence with N (the natural numbers). Note that this makes sense for finite sets. A set is countable if it is finite, or countably infinite. EXAMPLE {2, 4, 6, 8,...} {1, 3, 5, 7, 9,...}: f(x) =x 1. EXAMPLE N = {0, 1, 2, 3,...} {0, 2, 4, 6,...}: f(x) =2x. EXAMPLE {0, 2, 4, 6,...} {2, 4, 6,...}: f(x) =x +2. EXAMPLE {perfect squares} N: f(x) = x. Fact 11 An infinite set S is countably infinite iff it is possible to list all elements of S without repetitions, so that each s S appears with or without repetitions in the list. Alistisanotherrepresentationof abijection.

16 50 CHAPTER 4. SET THEORY EXAMPLE Evens: 0, 2, 4, 6, 10, 12,... EXAMPLE Odds: 1, 3, 5, 7, 9, 11,... EXAMPLE Squares: 0, 1, 2, 4, 9, 16,... EXAMPLE Rationals: Hmmm, we ll see! EXAMPLE Reals: No! this can t be done (not countably infinite). Now consider the Motel Infinity shown below with no vacancy: 1 can go to room 0 if everybody shifts down a room. Thus N { 1} N. Imagine instead of -1 we needed room for camp (Acountablyinfiniteset). Still we could free up enough room by moving for every i the occupant of room i to room 2i and giving the i-th person of the camp bus the room 2i +1. Fact 12 If A and B are countably infinite, then A B is countably infinite. What happens if a countably infinite number of camp buses need room in Motel Infinity? Rational Numbers are Countably Infinite By definition, rational numbers are those that can be written in the form p q where p and q are natural numbers and q 0. A naive attempt to enumerate all the rationals then can be to list them as 1 1, 1 2, 1 3, 1 4, 1 5,...,2 1, 2 2, 2 3, 2 4, 2 5,...,3 1, 3 2, 3 3, 3 4, 3 5,... But this does not work because the first part of the list ( 1 1, 1 2, 1 3, 1 4, 1 5,...)never finishes and therefore 2 1 is never reached. Asecondapproachwillbetousethetablebelow.

17 4.15. CARDINALITY OF INFINITE SETS 51 p q There is still a small problem with the above approach: some rationals are listed twice or more. Solution: Skip over those not in the lowest term. This way every positive rational appears in some box and we enumerate the boxes: 0 1,/0 2, 1 1,/0 3, 1 2, 2 1,/0 4, 1 3,/2 2, 3 1, Real Numbers are NOT Countably Infinite We will show that [0, 1] cannot be enumerated. This is due to George Cantor. Recall that each real number in [0, 1] can be represented as an infinite decimal 0.d 1 d 2 d 3 d 4 d 5 d 6...,whered i s are digits in {0,...,9}. EXAMPLE π 3= EXAMPLE 1 2 = Assume that there was an enumerate of reals in [0, 1]: r 1,r 2,r 3,...such that all reals in [0, 1] would appear exactly once. r r r r r n 0. d 1 d 2 d 3 d 4... d n d n+1 d n+2... Consider the real number r defined by diagonalizing. r =.b 1 b 2 b 3 b 4 b 4...

18 52 CHAPTER 4. SET THEORY where b i is 1 plus the i-th digit of r i (9 + 1 = 0). EXAMPLE For the table above we get r = r is a real number between 0 and 1 but was not listed because r r i for any i. Why? Because r and r i differ in decimal position i. Thus the enumeration wasn t one after all, contradicting the existence of such an enumeration Can All Functions Be Computed by Programs? Suppose our alphabet have 1000 characters. alphabet in order of their length. We can list all strings of this length 0 strings: 1 length 1 strings: 1,000 length 2 strings: 1,000,000 length 3 strings: Some but not all of these strings are computer programs. The shortest computer program that looks like this begin end. requires 10 characters. Thus we can enumerate all programs (plus some meaningless strings) and therefore the set of programs is countably infinite, i.e. {all programs} N. We like to show that there exists a function f that no program can computer it. We show even the stronger statement that there is some function that outputs a single digit and still cannot be computed by any program. Let F = {f : N {0, 1,...,9}}. Let us give some examples of such functions.

19 4.15. CARDINALITY OF INFINITE SETS 53 EXAMPLE f(x) = 1 (The constant function). EXAMPLE f(x) =x mod 10 (remainder of x divided by 10). EXAMPLE f(x) = first digit of x. { 0 if x is even EXAMPLE f(x) = 1 if x is odd How many such function do we have? Each function f : N {0,...,9} can be represented by a single real number in [0, 1]. This number is exactly 0.f(0)f(1)f(2)f(3)... EXAMPLE The function f shown be the table below x f(x) can be represented by the real number Conversely, each number in [0, 1] can be thought of as a function from the natural numbers to single digits. EXAMPLE The number 0.72 corresponds to the function f where f(0) = 7, f(1) = 2, and f(x) =0forx 2. Thus we have shown that F [0, 1] R. This means that there are much more many functions as there are programs and therefore, some functions are not computed by any programs.

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