CSci 2011 Discrete Mathematics Lecture 8 CSci 2011.

Slides:



Advertisements
Similar presentations
1 Sets CS/APMA 202, Spring 2005 Rosen, section 1.6 Aaron Bloomfield.
Advertisements

Prof. Johnnie Baker Module Basic Structures: Sets
Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Discrete Structures & Algorithms Basics of Set Theory EECE 320 — UBC.
Instructor: Hayk Melikya
(CSC 102) Discrete Structures Lecture 14.
Basic Structures: Sets, Functions, Sequences, Sums, and Matrices
Section 1.6: Sets Sets are the most basic of discrete structures and also the most general. Several of the discrete structures we will study are built.
2.1 Sets. DEFINITION 1 A set is an unordered collection of objects. DEFINITION 2 The objects in a set are called the elements, or members, of the set.
Discrete Structures Chapter 3 Set Theory Nurul Amelina Nasharuddin Multimedia Department.
Sets 1.
CSE115/ENGR160 Discrete Mathematics 02/10/11 Ming-Hsuan Yang UC Merced 1.
Sets 1.
Discrete Math 6A Max Welling. Recap 1. Proposition: statement that is true or false. 2. Logical operators: NOT, AND, OR, XOR, ,  3. Compound proposition:
CS 2210 (22C:019) Discrete Structures Sets and Functions Spring 2015 Sukumar Ghosh.
1 Set Operations CS/APMA 202, Spring 2005 Rosen, section 1.7 Aaron Bloomfield.
Sets.
Set theory Sets: Powerful tool in computer science to solve real world problems. A set is a collection of distinct objects called elements. Traditionally,
Methods of Proof & Proof Strategies
CSci 2011 Discrete Mathematics Lecture 3 CSci 2011.
1 Sets CS 202, Spring 2007 Epp, chapter 5 Aaron Bloomfield.
CSci 2011 Discrete Mathematics Lecture 6
1 Methods of Proof. 2 Consider (p  (p→q)) → q pqp→q p  (p→q)) (p  (p→q)) → q TTTTT TFFFT FTTFT FFTFT.
Set, Combinatorics, Probability & Number Theory Mathematical Structures for Computer Science Chapter 3 Copyright © 2006 W.H. Freeman & Co.MSCS Slides Set,
CS 103 Discrete Structures Lecture 10 Basic Structures: Sets (1)
Discrete Structure Sets. 2 Set Theory Set: Collection of objects (“elements”) a  A “a is an element of A” “a is a member of A” a  A “a is not an element.
DISCRETE COMPUTATIONAL STRUCTURES
Mathematical Proofs. Chapter 1 Sets 1.1 Describing a Set 1.2 Subsets 1.3 Set Operations 1.4 Indexed Collections of Sets 1.5 Partitions of Sets.
CS201: Data Structures and Discrete Mathematics I
Chapter 2: Basic Structures: Sets, Functions, Sequences, and Sums (1)
CompSci 102 Discrete Math for Computer Science
ELEMENTARY SET THEORY.
Chapter SETS DEFINITION OF SET METHODS FOR SPECIFYING SET SUBSETS VENN DIAGRAM SET IDENTITIES SET OPERATIONS.
Chapter 2 With Question/Answer Animations. Section 2.1.
Rosen 1.6, 1.7. Basic Definitions Set - Collection of objects, usually denoted by capital letter Member, element - Object in a set, usually denoted by.
Discrete Mathematics SETS. What is a set? ^A set is a unordered collection of “objects”  People in a class: {A yşe, B arış, C anan }  Cities in Turkey.
(CSC 102) Lecture 13 Discrete Structures. Previous Lectures Summary  Direct Proof  Indirect Proof  Proof by Contradiction  Proof by Contra positive.
Sets Definition: A set is an unordered collection of objects, called elements or members of the set. A set is said to contain its elements. We write a.
Based on slides by Patrice Belleville and Steve Wolfman CPSC 121: Models of Computation Unit 11: Sets.
Discrete Mathematics Set.
CSci 2011 Discrete Mathematics Lecture 9, 10
Based on slides by Patrice Belleville and Steve Wolfman CPSC 121: Models of Computation Unit 11: Sets.
CSci 2011 Discrete Mathematics Lecture 4 CSci 2011.
CSE 311: Foundations of Computing Fall 2013 Lecture 8: Proofs and Set theory.
Module #3 - Sets 3/2/2016(c) , Michael P. Frank 2. Sets and Set Operations.
Discrete Mathematics CS 2610 August 31, Agenda Set Theory Set Builder Notation Universal Set Power Set and Cardinality Set Operations Set Identities.
Proof Review CS 202 Aaron Bloomfield Spring 2007.
CSci 2011 Discrete Mathematics Lecture 5 CSci 2011.
Thinking Mathematically Venn Diagrams and Set Operations.
Chapter 2 1. Chapter Summary Sets (This Slide) The Language of Sets - Sec 2.1 – Lecture 8 Set Operations and Set Identities - Sec 2.2 – Lecture 9 Functions.
Introduction to Set Theory (§1.6) A set is a new type of structure, representing an unordered collection (group, plurality) of zero or more distinct (different)
CPCS 222 Discrete Structures I
Sets CS 202, Spring 2007 Epp, chapter 5.
CSE15 Discrete Mathematics 02/13/17
Dr. Ameria Eldosoky Discrete mathematics
Applied Discrete Mathematics Week 1: Logic and Sets
Set Definition: A set is unordered collection of objects.
Set, Combinatorics, Probability & Number Theory
Sets Section 2.1.
CS 2210:0001 Discrete Structures Sets and Functions
Chapter 1 Logic and Proofs Homework 2 Given the statement “A valid password is necessary for you to log on to the campus server.” Express the statement.
Taibah University College of Computer Science & Engineering Course Title: Discrete Mathematics Code: CS 103 Chapter 2 Sets Slides are adopted from “Discrete.
Exercises Show that (P  Q)  (P)  (Q)
CS100: Discrete structures
Propositional Logic Defining Propositional Logic
2.1 Sets Dr. Halimah Alshehri.
Discrete Mathematics R. Johnsonbaugh
Sets & Set Operations.
Logic Logic is a discipline that studies the principles and methods used to construct valid arguments. An argument is a related sequence of statements.
CSC102 - Discrete Structures (Discrete Mathematics) Set Operations
Presentation transcript:

CSci 2011 Discrete Mathematics Lecture 8 CSci 2011

Admin ^Due dates and quiz  Groupwork 4 is due on Oct 5 th.  Homework 3 is due on Oct 14 th.  Quiz 2: Oct 7 rd.  1 page cheat sheet is allowed. ^  Put [2011] in front. ^Me and Aziz will be out of town next week.  No office hour for Yongdae  Aziz’s office hour will be replaced by someone. ^Check class web site  Read syllabus, Use forum. ^Study Guides

CSci 2011 Recap ^Propositional operation summary ^Check translation ^Definition  Tautology, Contradiction, logical equicalence not andorconditionalBi-conditional pq ppqqpqpqpqpqpqpqpqpq TTFFTTTT TFFTFTFF FTTFFTTF FFTTFFTT

CSci 2011 Recap p  T  p p  F  p Identity Laws (p  q)  r  p  (q  r) (p  q)  r  p  (q  r) Associative laws p  T  T p  F  F Domination Law p  (q  r)  (p  q)  (p  r) p  (q  r)  (p  q)  (p  r) Distributive laws p  p  p p  p  p Idempotent Laws  (p  q)   p   q  (p  q)   p   q De Morgan’s laws ( p)  p Double negation law p  (p  q)  p p  (p  q)  p Absorption laws p  q  q  p p  q  q  p Commutative Laws p   p  T p   p  F Negation lows pq  pq Definition of Implication p  q  (p  q)  (q  p) Definition of Biconditional

Recap ^Quantifiers  Universal quantifier: x P(x)  Negating quantifiers  ¬x P(x) = x ¬P(x)  ¬x P(x) = x ¬P(x) xy P(x, y)  Nested quantifiers  xy P(x, y): “For all x, there exists a y such that P(x,y)”  xy P(x,y): There exists an x such that for all y P(x,y) is true”  ¬  x P(x) =  x ¬P(x), ¬  x P(x) =  x ¬P(x) ^Proof techniques  Direct proof  Indirect Proof CSci 2011

Recap Modus ponens p p  q  q Modus tollens  q p  q   p Hypothetical syllogism p  q q  r  p  r Disjunctive syllogism p  q  p  q Addition p  p  q Simplification p  q  p Conjunction p q  p  q Resolution p  q  p  r  q  r

Recap ^p → q  Direct Proof: Assume p is true. Show that q is also true.  Indirect Proof: Assume ¬q is true. Show that p is true. ^Proof by contradiction  Proving p: Assume p is not true. Find a contradiction.  Proving p → q  ¬(p → q)  (p  q)  p  ¬q  Assume p is tue and q is not true. Find a contradiction.  Proof by Cases: [(p 1 p 2 …p n )q]  [(p 1 q)(p 2 q)…(p n q)]  If and only if proof: pq (p → q)(q → p) ^Existence Proof  Constructive vs. Non-constructive Proof CSci 2011

Uniqueness proofs ^A theorem may state that only one such value exists ^To prove this, you need to show:  Existence: that such a value does indeed exist  Either via a constructive or non-constructive existence proof  Uniqueness: that there is only one such value

CSci 2011 Uniqueness proof example ^If the real number equation 5x+3=a has a solution then it is unique ^Existence  We can manipulate 5x+3=a to yield x=(a-3)/5  Is this constructive or non-constructive? ^Uniqueness  If there are two such numbers, then they would fulfill the following: a = 5x+3 = 5y+3  We can manipulate this to yield that x = y  Thus, the one solution is unique!

CSci 2011 Forward and Backward Reasoning ^(x+y) / 2 > √xy for all distinct positive real number x and y.

CSci 2011 Counterexamples ^Given a universally quantified statement, find a single example which it is not true ^Note that this is DISPROVING a UNIVERSAL statement by a counterexample ^x ¬R(x), where R(x) means “x has red hair”  Find one person (in the domain) who has red hair ^Every positive integer is the square of another integer  The square root of 5 is 2.236, which is not an integer

CSci 2011 What’s wrong with this proof? ^If n 2 is an even integer, then n is an even integer. Proof) Suppose n 2 is even. Then n 2 = 2 k for some integer k. Let n = 2 l for some integer l. Then n is an even integer.

CSci 2011 Proof methods ^We will discuss ten proof methods: 1.Direct proofs 2.Indirect proofs 3.Vacuous proofs 4.Trivial proofs 5.Proof by contradiction 6.Proof by cases 7.Proofs of equivalence 8.Existence proofs 9.Uniqueness proofs 10.Counterexamples

ch2.1 Sets CSci 2011

What is a set? ^A set is a unordered collection of “objects”  People in a class: {Alice, Bob, Chris }  States in the US: {Alabama, Alaska, Virginia, … }  Sets can contain non-related elements: {3, a, red, Virginia } ^We will most often use sets of numbers  All positive numbers less than or equal to 5: {1, 2, 3, 4, 5}  A few selected real numbers: { 2.1, π, 0, -6.32, e } ^Properties  Order does not matter  {1, 2, 3, 4, 5} is equivalent to {3, 5, 2, 4, 1}  Sets do not have duplicate elements  Consider the list of students in this class –It does not make sense to list somebody twice

CSci 2011 Specifying a Set ^Capital letters (A, B, S…) for sets ^Italic lower-case letter for elements (a, x, y…) ^Easiest way: list all the elements  A = {1, 2, 3, 4, 5}, Not always feasible! ^May use ellipsis (…): B = {0, 1, 2, 3, …}  May cause confusion. C = {3, 5, 7, …}. What’s next?  If the set is all odd integers greater than 2, it is 9  If the set is all prime numbers greater than 2, it is 11 ^Can use set-builder notation  D = {x | x is prime and x > 2}  E = {x | x is odd and x > 2}  The vertical bar means “such that”

CSci 2011 Specifying a set ^A set “contains” the various “members” or “elements” that make up the set  If an element a is a member of (or an element of) a set S, we use then notation a  S  4  {1, 2, 3, 4}  If not, we use the notation a  S  7  {1, 2, 3, 4}

CSci 2011 Often used sets ^N = {0, 1, 2, 3, …} is the set of natural numbers ^Z = {…, -2, -1, 0, 1, 2, …} is the set of integers ^Z + = {1, 2, 3, …} is the set of positive integers (a.k.a whole numbers)  Note that people disagree on the exact definitions of whole numbers and natural numbers ^Q = {p/q | p  Z, q  Z, q ≠ 0} is the set of rational numbers  Any number that can be expressed as a fraction of two integers (where the bottom one is not zero) ^R is the set of real numbers

CSci 2011 The universal set 1  U is the universal set – the set of all of elements (or the “universe”) from which given any set is drawn  For the set {-2, 0.4, 2}, U would be the real numbers  For the set {0, 1, 2}, U could be the N, Z, Q, R depending on the context  For the set of the vowels of the alphabet, U would be all the letters of the alphabet

CSci 2011 Venn diagrams ^Represents sets graphically  The box represents the universal set  Circles represent the set(s) ^Consider set S, which is the set of all vowels in the alphabet ^The individual elements are usually not written in a Venn diagram a ei ou b c df g hj kl m npq rst vwx yz U S

CSci 2011 Sets of sets ^Sets can contain other sets  S = { {1}, {2}, {3} }  T = { {1}, {{2}}, {{{3}}} }  V = { {{1}, {{2}}}, {{{3}}}, { {1}, {{2}}, {{{3}}} } }  V has only 3 elements! ^Note that 1 ≠ {1} ≠ {{1}} ≠ {{{1}}}  They are all different

CSci 2011 The Empty Set ^If a set has zero elements, it is called the empty (or null) set  Written using the symbol   Thus,  = { }  VERY IMPORTANT ^It can be a element of other sets  { , 1, 2, 3, x } is a valid set ^ ≠ {  }  The first is a set of zero elements  The second is a set of 1 element ^Replace  by { }, and you get: { } ≠ {{ }}  It’s easier to see that they are not equal that way

CSci 2011 Set Equality, Subsets ^Two sets are equal if they have the same elements  {1, 2, 3, 4, 5} = {5, 4, 3, 2, 1}  {1, 2, 3, 2, 4, 3, 2, 1} = {4, 3, 2, 1}  Two sets are not equal if they do not have the same elements  {1, 2, 3, 4, 5} ≠ {1, 2, 3, 4} ^If all the elements of a set S are also elements of a set T, then S is a subset of T  If S = {2, 4, 6}, T = {1, 2, 3, 4, 5, 6, 7}, S is a subset of T  This is specified by S  T meaning that  x (x  S  x  T)  For any set S, S  S (S S  S)  For any set S,   S (S   S)

CSci 2011 ^If S is a subset of T, and S is not equal to T, then S is a proper subset of T  Can be written as: R  T and R  T  Let T = {0, 1, 2, 3, 4, 5}  If S = {1, 2, 3}, S is not equal to T, and S is a subset of T  A proper subset is written as S  T  Let Q = {4, 5, 6}. Q is neither a subset or T nor a proper subset of T ^The difference between “subset” and “proper subset” is like the difference between “less than or equal to” and “less than” for numbers Proper Subsets

CSci 2011 Set cardinality ^The cardinality of a set is the number of elements in a set, written as |A| ^Examples  Let R = {1, 2, 3, 4, 5}. Then |R| = 5  || = 0  Let S = {, {a}, {b}, {a, b}}. Then |S| = 4

CSci 2011 Power Sets ^Given S = {0, 1}. All the possible subsets of S?   (as it is a subset of all sets), {0}, {1}, and {0, 1}  The power set of S (written as P(S)) is the set of all the subsets of S  P(S) = { , {0}, {1}, {0,1} }  Note that |S| = 2 and |P(S)| = 4 ^Let T = {0, 1, 2}. The P(T) = { , {0}, {1}, {2}, {0,1}, {0,2}, {1,2}, {0,1,2} }  Note that |T| = 3 and |P(T)| = 8 ^P() = {  }  Note that || = 0 and |P()| = 1 ^If a set has n elements, then the power set will have 2 n elements

CSci 2011 Tuples ^In 2-dimensional space, it is a (x, y) pair of numbers to specify a location ^In 3-dimensional (1,2,3) is not the same as (3,2,1) – space, it is a (x, y, z) triple of numbers ^In n-dimensional space, it is a n-tuple of numbers  Two-dimensional space uses pairs, or 2-tuples  Three-dimensional space uses triples, or 3-tuples ^Note that these tuples are ordered, unlike sets  the x value has to come first +x +y (2,3)

CSci 2011 Cartesian products ^A Cartesian product is a set of all ordered 2-tuples where each “part” is from a given set  Denoted by A x B, and uses parenthesis (not curly brackets)  For example, 2-D Cartesian coordinates are the set of all ordered pairs Z x Z  Recall Z is the set of all integers  This is all the possible coordinates in 2-D space  Example: Given A = { a, b } and B = { 0, 1 }, what is their Cartiesian product?  C = A x B = { (a,0), (a,1), (b,0), (b,1) } ^Formal definition of a Cartesian product:  A x B = { (a,b) | a  A and b  B }

CSci 2011 Cartesian Products 2 ^All the possible grades in this class will be a Cartesian product of the set S of all the students in this class and the set G of all possible grades  Let S = { Alice, Bob, Chris } and G = { A, B, C }  D = { (Alice, A), (Alice, B), (Alice, C), (Bob, A), (Bob, B), (Bob, C), (Chris, A), (Chris, B), (Chris, C) }  The final grades will be a subset of this: { (Alice, C), (Bob, B), (Chris, A) }  Such a subset of a Cartesian product is called a relation (more on this later in the course)

ch2.2 Set Operations CSci 2011

Set operations: Union ^Formal definition for the union of two sets: A U B = { x | x  A or x  B } ^Further examples  {1, 2, 3} U {3, 4, 5} = {1, 2, 3, 4, 5}  {a, b} U {3, 4} = {a, b, 3, 4}  {1, 2} U  = {1, 2} ^Properties of the union operation  A U  = AIdentity law  A U U = U Domination law  A U A = AIdempotent law  A U B = B U ACommutative law  A U (B U C) = (A U B) U CAssociative law

CSci 2011 Set operations: Intersection ^Formal definition for the intersection of two sets: A ∩ B = { x | x  A and x  B } ^Examples  {1, 2, 3} ∩ {3, 4, 5} = {3}  {a, b} ∩ {3, 4} =   {1, 2} ∩  =  ^Properties of the intersection operation  A ∩ U = AIdentity law  A ∩  =  Domination law  A ∩ A = AIdempotent law  A ∩ B = B ∩ ACommutative law  A ∩ (B ∩ C) = (A ∩ B) ∩ CAssociative law

CSci 2011 Disjoint sets ^Formal definition for disjoint sets: two sets are disjoint if their intersection is the empty set ^Further examples  {1, 2, 3} and {3, 4, 5} are not disjoint  {a, b} and {3, 4} are disjoint  {1, 2} and  are disjoint  Their intersection is the empty set   and  are disjoint!  Their intersection is the empty set

CSci 2011 ^Formal definition for the difference of two sets: A - B = { x | x  A and x  B } ^Further examples  {1, 2, 3} - {3, 4, 5} = {1, 2}  {a, b} - {3, 4} = {a, b}  {1, 2} -  = {1, 2}  The difference of any set S with the empty set will be the set S Set operations: Difference

CSci 2011 Complement sets ^Formal definition for the complement of a set: A = { x | x  A } = A c  Or U – A, where U is the universal set  Further examples (assuming U = Z)  {1, 2, 3} c = { …, -2, -1, 0, 4, 5, 6, … }  {a, b} c = Z ^Properties of complement sets  (A c ) c = AComplementation law  A U A c = U Complement law  A ∩ A c = Complement law

CSci 2011 Set identities A = A AU = A Identity Law AU = U A =  Domination law AA = A AA = A Idempotent Law (A c ) c = A Complement Law AB = BA AB = BA Commutative Law (AB) c = A c B c (AB) c = A c B c De Morgan’s Law A(BC) = (AB)C A(BC) = (AB)C Associative Law A(BC) = (AB)(AC) A(BC) = (AB)(AC) Distributive Law A(AB) = A A(AB) = A Absorption Law A  A c = U A  A c =  Complement Law

CSci 2011 How to prove a set identity ^For example: A ∩ B=B-(B-A) ^Four methods:  Use the basic set identities  Use membership tables  Prove each set is a subset of each other  Use set builder notation and logical equivalences

CSci 2011 What we are going to prove… A ∩ B=B-(B-A) AB A∩BA∩BB-AB-(B-A)

CSci 2011 Proof by Set Identities  A  B = A - (A - B) Proof) A - (A - B) = A - (A  B c ) = A  (A  B c ) c = A  (A c  B) = (A  A c )  (A  B) =   (A  B) = A  B

CSci 2011 Showing each is a subset of the others  (A  B) c = A c  B c Proof) Want to prove that (A  B) c  A c  B c and (A  B) c  A c  B c x  (A  B) c  x  (A  B)   (x  A  B)   (x  A  x  B)   (x  A)   (x  B)  x  A  x  B  x  A c  x  B c  x  A c  B c

CSci 2011 Examples ^Let A, B, and C be sets. Show that: a)(AUB)  (AUBUC) b)(A ∩ B ∩ C)  (A ∩ B) c)(A-B)-C  A-C d)(A-C) ∩ (C-B) = 