Lecture 9. The Principle of Inclusion/Exclusion. 9.1 Introduction: a familiar example
|
|
- Arthur Watson
- 6 years ago
- Views:
Transcription
1 Lecture 9 he Principle of Inclusion/Exclusion hese notes are based on a pair of lectures originally written by (Manchester s own) Prof. Nige Ray. Reading: he Principle of Inclusion/Exclusion appears in the first year module Foundations of Pure Mathematics, but it is also a standard technique in Combinatorics and so is discussed in many other books 1. he Wikipedia article, which gives a version of the proof in Section below, is also a good place to start. 9.1 Introduction: a familiar example Suppose we have some finite universal set U and two subsets, 1 U and 2 U. If the subsets are disjoint then it s easy to work out the number of elements in their union: 1 \ 2 ; ) 1 [ he case where the subsets have a non-empty intersection provides the simplest instance of the result we re going to develop today, the Principle of Inclusion/Exclusion. You may already know a similar result from Probability. Lemma 9.1 (Inclusion/Exclusion for two sets). If 1 and 2 are finite sets then 1 [ \ 2. (9.1) Note that this formula, which is illustrated in Figure 9.1, works even 1 \ 2 ;, as then 1 \ 2 0. Proof. o prove this result, note that the sum counts each member of the intersection 1 \ 2 twice, once as a member of 1 and then again as a member 1 See, for example, Dossey, Otto, Spence, and Vanden Eynden (2006), Discrete Mathematics or, for a short, clear account, Anderson (1974), A First Course in Combinatorial Mathematics. 9.1
2 U U Figure 9.1: In the example at left 1 \ 2 ;, so 1 [ , but in the example at right 1 \ 2 6 ; and so 1 [ \ 2 < U 1 \ \ 1 Figure 9.2: Here 1 \ 2 and 1 \ 2 are shown in shades of blue, while 2 \ 1 is in yellow. of 2. Subtracting 1 \ 2 corrects for this double-counting. Alternatively, for those who prefer proofs that look more like calculations, begin by defining 1 \ 2 {x 2 U x 2 1, but x/2 2 }. hen, as is illustrated in Figure 9.2, 1 ( 1 \ 2 ) [ ( 1 \ 2 ). Further, the sets 1 \ 2 and 1 \ 2 are disjoint by construction, so 1 1 \ \ 2 or 1 \ \ 2. (9.2) Similarly, 1 \ 2 and 2 are disjoint and 1 [ 2 ( 1 \ 2 ) [ 2 so 1 [ 2 1 \ \ \ 2 where, in passing from the first line to the second, we have used (9.2). he last line is the result we were trying to prove, so we are finished. 9.2 Principle and proof Before moving to the general case, let s consider one more small example, this time with three subsets 1, 2 and 3 : we can handle this case by clever use 9.2
3 U Figure 9.3: In the diagram above all of the intersections appearing in Eqn. (9.3) are nonempty. of Lemma 9.1 from the previous section. If we regard ( 1 [ 2 )asasinglesetand 3 as a second set, then Eqn. (9.1) says ( 1 [ 2 ) [ 3 ( 1 [ 2 ) + 3 ( 1 [ 2 ) \ 3 ( \ 2 )+ 3 ( 1 [ 2 ) \ \ 2 ( 1 [ 2 ) \ 3 Focusing on the final term, we can use standard relations about unions and intersections to say ( 1 [ 2 ) \ 3 ( 1 \ 3 ) [ ( 2 \ 3 ). hen, applying Eqn. (9.1) to the pair of sets ( 1 \ 3 )and( 2 \ 3 ), we obtain ( 1 [ 2 ) \ 3 ( 1 \ 3 ) [ ( 2 \ 3 ) 1 \ \ 3 ( 1 \ 3 ) \ ( 2 \ 3 ) 1 \ \ 3 1 \ 2 \ 3 where, in going from the second line to the third, we have used ( 1 \ 3 ) \ ( 2 \ 3 ) 1 \ 2 \ 3. Finally, putting all these results together, we obtain the analogue of Eqn. (9.1) for three subsets: ( 1 [ 2 ) [ \ 2 ( 1 [ 2 ) \ \ 3 ( 1 \ \ 3 ( 1 \ 2 \ 3 ) ( ) ( 1 \ \ \ 3 ) + 1 \ 2 \ 3. (9.3) Figure 9.3 helps make sense of this formula and prompts the following observations: 9.3
4 Elements of 1 [ 2 [ 3 that belong to exactly one of the j are counted exactly once by the sum ( ) and do not contribute to any of the terms involving intersections. Elements of 1 [ 2 [ 3 that belong to exactly two of the j are doublecounted by the sum, ( ), but this double-counting is corrected by the term involving two-fold intersections. Finally, elements of 1 [ 2 [ 3 that belong to all three of the sets are triple-counted by the initial sum ( ). his triple-counting is then completely cancelled by the term involving two-fold intersections. hen, finally, this cancellation is repaired by the final term, which counts each such element once he general case he Principle of Inclusion/Exclusion generalises the results in Eqns. (9.1) and (9.3) to unions of arbitrarily many subsets. heorem 9.2 (he Principle of Inclusion/Exclusion). If U is a finite set and { j } n j1 is a collection of n subsets, then n[ j 1 [ [ n j1 or, more concisely, n 1 \ 2 n 1 \ n + 1 \ 2 \ n 2 \ n 1 \ n +( 1) m 1.. 1applei 1 apple applei mapplen i1 \ \ im +( 1) n 1 1 \ \ n (9.4) 1 [ [ n One can prove this in at least two ways: I {1,...,n},I6;( 1) I 1 \ i2i i (9.5) by induction, with a calculation that is essentially the same as the one used to obtain the n 3case Eqn.(9.3) fromthen 2one Eqn.(9.1); by showing that each x 2 1 [ [ n contributes exactly one to the sum on the right hand side of Eqn. (9.5). he first approach is straightforward, if a bit tedious, and so is left as an exercise, but the second is more interesting and so it s the one we ll study here. 9.4
5 9.2.2 Proof he key idea is to think of the the elements of 1 [ [ n individually and ask what each one contributes to the sum in Eqn. (9.5). Suppose that an element x 2 1 [ [ n belongs to exactly of the subsets, with 1 apple apple n: we will prove that x makes a net contribution of 1. For the sake of concreteness, we ll say x 2 i1,..., i where i 1,...,i are distinct elements of {1,...,n}. As we ve assumed that x belongs to exactly of the subsets j, it contributes atotalof to the first row, n, of the long sum in Eqn. (9.4). Further, x contributes a total of to the sum in the row involving two-way 2 intersections 1 \ 2 n 1 \ n. o see this, note that if x 2 j \ k then both j and k must be members of the set {i 1,...,i}. Similar arguments show that if k apple, then x contributes a total of! k k!( k)! to the sum in the row of Eqn. (9.4) that involves k-fold intersections. Finally, for k> there are no k-fold intersections that contain x and so x makes a contribution of zero to the corresponding rows in Eqn. (9.4). Putting these observations together we see that x make a net contribution of ( 1) 1 (9.6) 2 3 his sum can be made to look more familiar by considering the following application of the Binomial heorem: hus or 0 (1 1) ( 1) j (1) j j j ( 1) apple ( 1) ( 1) 1 he left hand side here is the same as the sum in Eqn. (9.6) and so we ve established that any x which belongs to exactly of the subsets j makes a net contribution of 1 to the sum on the right hand side of Eqn. (9.5). And as every x 2 1 [ [ n must belong to at least one of the j, this establishes the Principle of Inclusion/Exclusion. 9.5
6 9.2.3 Alternative proof Students who like proofs that look more like calculations may prefer to reformulate the arguments from the previous section in terms of characteristic functions (sometimes also called indicator functions) ofsets.ifwedefine : U! {0, 1} by 1 if s 2 (s) 0 otherwise then we can calculate for a subset U as follows: (x) x2u! (x) + x2 x/2 x2 (x)! (x) (9.7) where, in passing from the second to third lines, I have dropped the second sum because all its terms are zero. hen the Principle of Inclusion/Exclusion is equivalent to x2 1 [ [ n 1 [ [ n (x) i 1) I {1,...,n},I6;( \ I 1 i2i ( 1) I 1 I {1,...,n},I6; n x2 i2i i i2i i (x) x2 i2i i 1 i2i (x) A i which I have obtained by using of Eqn. (9.7) to replace terms in Eqn. (9.5) with the corresponding sums of values of characteristic functions. We can then rearrange the expression on the right, first expanding the ranges of the sums over elements of k-fold intersections (this doesn t change the result since (x) 0 for x /2 ) andtheninterchangingtheorderofsummationsothat the sum over elements comes first. his calculation proves that the Principle of Inclusion/Exclusion is equivalent to the following: x2 1 [ [ n 1 [ [ n (x) n x2 1 [ [ n n 9.6 x2 1 [ [ n i2i i (x)! i2i (x) (9.8) i
7 Arguments similar to those in Section then establish the following results, the last of which, along with Eqn. (9.8), proves heorem 9.2. Proposition 9.3. If an element x 2 1 [ [ n belongs to exactly of the sets { j } n j1 then for k apple we have i2i (x) i k! k!( k)! while if k> i2i (x) 0 i Proposition 9.4. For an element x 2 1 [ [ n we have n i2i i (x) n k 1. Lemma 9.5. he characteristic function 1 [ [ n of the set 1 [ [ n satisfies 1 [ [ n (x) 9.3 An example n i2i i (x). How many of the integers n with 1 apple n apple 150 are relatively prime to 70? his is a job for the Principle of Inclusion/Exclusion. First note that the prime factorization of 70 is Now consider a universal set U {1,...,150} and three subsets 1, 2 and 3 consisting of multiples of 2, 5 and 7, respectively. A member of U that shares a prime factor with 70 belongs to at least one of the j and so the number we re after is U 1 [ 2 [ 3 U ( ) +( 1 \ \ \ 3 ) 1 \ 2 \ ( ) + ( ) (9.9) where I have used the numbers in able 9.1 which lists the various cardinalities that we need. 9.7
8 Set Description Cardinality 1 multiples of multiples of multiples of \ 2 multiples of \ 3 multiples of \ 3 multiples of \ 2 \ 3 multiples of 70 2 able 9.1: Eqn. (9.9). he sizes of the various intersections needed for the calculation in 9.8
The integers. Chapter 3
Chapter 3 The integers Recall that an abelian group is a set A with a special element 0, and operation + such that x +0=x x + y = y + x x +y + z) =x + y)+z every element x has an inverse x + y =0 We also
More information5 Set Operations, Functions, and Counting
5 Set Operations, Functions, and Counting Let N denote the positive integers, N 0 := N {0} be the non-negative integers and Z = N 0 ( N) the positive and negative integers including 0, Q the rational numbers,
More informationLECTURE 13. Quotient Spaces
LECURE 13 Quotient Spaces In all the development above we have created examples of vector spaces primarily as subspaces of other vector spaces Below we ll provide a construction which starts with a vector
More informationHomework 1 2/7/2018 SOLUTIONS Exercise 1. (a) Graph the following sets (i) C = {x R x in Z} Answer:
Homework 1 2/7/2018 SOLTIONS Eercise 1. (a) Graph the following sets (i) C = { R in Z} nswer: 0 R (ii) D = {(, y), y in R,, y 2}. nswer: = 2 y y = 2 (iii) C C nswer: y 1 2 (iv) (C C) D nswer: = 2 y y =
More informationLecture 3: Miscellaneous Techniques
Lecture 3: Miscellaneous Techniques Rajat Mittal IIT Kanpur In this document, we will take a look at few diverse techniques used in combinatorics, exemplifying the fact that combinatorics is a collection
More informationLECTURE 13. Quotient Spaces
LECURE 13 Quotient Spaces In all the development above we have created examples of vector spaces primarily as subspaces of other vector spaces Below we ll provide a construction which starts with a vector
More informationCounting in the Twilight Zone
Chapter 17 Counting in the Twilight Zone In Volume 1 we examined a great many counting methods, but all were based on the rock of common sense. In this chapter we will look at counting methods which go
More informationCISC 1100: Structures of Computer Science
CISC 1100: Structures of Computer Science Chapter 2 Sets and Sequences Fordham University Department of Computer and Information Sciences Fall, 2010 CISC 1100/Fall, 2010/Chapter 2 1 / 49 Outline Sets Basic
More informationCosets and Lagrange s theorem
Cosets and Lagrange s theorem These are notes on cosets and Lagrange s theorem some of which may already have been lecturer. There are some questions for you included in the text. You should write the
More informationIn N we can do addition, but in order to do subtraction we need to extend N to the integers
Chapter 1 The Real Numbers 1.1. Some Preliminaries Discussion: The Irrationality of 2. We begin with the natural numbers N = {1, 2, 3, }. In N we can do addition, but in order to do subtraction we need
More informationIn N we can do addition, but in order to do subtraction we need to extend N to the integers
Chapter The Real Numbers.. Some Preliminaries Discussion: The Irrationality of 2. We begin with the natural numbers N = {, 2, 3, }. In N we can do addition, but in order to do subtraction we need to extend
More informationWHY POLYNOMIALS? PART 1
WHY POLYNOMIALS? PART 1 The proofs of finite field Kakeya and joints and short and clean, but they also seem strange to me. They seem a little like magic tricks. In particular, what is the role of polynomials
More informationn n P} is a bounded subset Proof. Let A be a nonempty subset of Z, bounded above. Define the set
1 Mathematical Induction We assume that the set Z of integers are well defined, and we are familiar with the addition, subtraction, multiplication, and division. In particular, we assume the following
More informationMATH 115, SUMMER 2012 LECTURE 12
MATH 115, SUMMER 2012 LECTURE 12 JAMES MCIVOR - last time - we used hensel s lemma to go from roots of polynomial equations mod p to roots mod p 2, mod p 3, etc. - from there we can use CRT to construct
More informationCDM Combinatorial Principles
CDM Combinatorial Principles 1 Counting Klaus Sutner Carnegie Mellon University Pigeon Hole 22-in-exclusion 2017/12/15 23:16 Inclusion/Exclusion Counting 3 Aside: Ranking and Unranking 4 Counting is arguably
More informationPart V. Chapter 19. Congruence of integers
Part V. Chapter 19. Congruence of integers Congruence modulo m Let m be a positive integer. Definition. Integers a and b are congruent modulo m if and only if a b is divisible by m. For example, 1. 277
More informationADVANCED CALCULUS - MTH433 LECTURE 4 - FINITE AND INFINITE SETS
ADVANCED CALCULUS - MTH433 LECTURE 4 - FINITE AND INFINITE SETS 1. Cardinal number of a set The cardinal number (or simply cardinal) of a set is a generalization of the concept of the number of elements
More information1. SET 10/9/2013. Discrete Mathematics Fajrian Nur Adnan, M.CS
1. SET 10/9/2013 Discrete Mathematics Fajrian Nur Adnan, M.CS 1 Discrete Mathematics 1. Set and Logic 2. Relation 3. Function 4. Induction 5. Boolean Algebra and Number Theory MID 6. Graf dan Tree/Pohon
More informationMA554 Assessment 1 Cosets and Lagrange s theorem
MA554 Assessment 1 Cosets and Lagrange s theorem These are notes on cosets and Lagrange s theorem; they go over some material from the lectures again, and they have some new material it is all examinable,
More informationMath Lecture 18 Notes
Math 1010 - Lecture 18 Notes Dylan Zwick Fall 2009 In our last lecture we talked about how we can add, subtract, and multiply polynomials, and we figured out that, basically, if you can add, subtract,
More information11 Division Mod n, Linear Integer Equations, Random Numbers, The Fundamental Theorem of Arithmetic
11 Division Mod n, Linear Integer Equations, Random Numbers, The Fundamental Theorem of Arithmetic Bezout s Lemma Let's look at the values of 4x + 6y when x and y are integers. If x is -6 and y is 4 we
More informationWeek 2: Counting with sets; The Principle of Inclusion and Exclusion (PIE) 13 & 15 September 2017
(1/25) MA204/MA284 : Discrete Mathematics Week 2: Counting with sets; The Principle of Inclusion and Exclusion (PIE) Dr Niall Madden 13 & 15 September 2017 A B A B C Tutorials (2/25) Tutorials will start
More informationThe Inclusion Exclusion Principle and Its More General Version
The Inclusion Exclusion Principle and Its More General Version Stewart Weiss June 28, 2009 1 Introduction The Inclusion-Exclusion Principle is typically seen in the context of combinatorics or probability
More informationSET THEORY. Disproving an Alleged Set Property. Disproving an Alleged Set. Example 1 Solution CHAPTER 6
CHAPTER 6 SET THEORY SECTION 6.3 Disproofs, Algebraic Proofs, and Boolean Algebras Copyright Cengage Learning. All rights reserved. Copyright Cengage Learning. All rights reserved. Disproving an Alleged
More informationCPSC 536N: Randomized Algorithms Term 2. Lecture 9
CPSC 536N: Randomized Algorithms 2011-12 Term 2 Prof. Nick Harvey Lecture 9 University of British Columbia 1 Polynomial Identity Testing In the first lecture we discussed the problem of testing equality
More information2. Sets. 2.1&2.2: Sets and Subsets. Combining Sets. c Dr Oksana Shatalov, Spring
c Dr Oksana Shatalov, Spring 2015 1 2. Sets 2.1&2.2: Sets and Subsets. Combining Sets. Set Terminology and Notation DEFINITIONS: Set is well-defined collection of objects. Elements are objects or members
More informationIn this initial chapter, you will be introduced to, or more than likely be reminded of, a
1 Sets In this initial chapter, you will be introduced to, or more than likely be reminded of, a fundamental idea that occurs throughout mathematics: sets. Indeed, a set is an object from which every mathematical
More informationa (b + c) = a b + a c
Chapter 1 Vector spaces In the Linear Algebra I module, we encountered two kinds of vector space, namely real and complex. The real numbers and the complex numbers are both examples of an algebraic structure
More informationIntroduction to Set Operations
Introduction to Set Operations CIS008-2 Logic and Foundations of Mathematics David Goodwin david.goodwin@perisic.com 12:00, Friday 21 st October 2011 Outline 1 Recap 2 Introduction to sets 3 Class Exercises
More informationMATH 115, SUMMER 2012 LECTURE 4 THURSDAY, JUNE 21ST
MATH 115, SUMMER 2012 LECTURE 4 THURSDAY, JUNE 21ST JAMES MCIVOR Today we enter Chapter 2, which is the heart of this subject. Before starting, recall that last time we saw the integers have unique factorization
More informationSets. Introduction to Set Theory ( 2.1) Basic notations for sets. Basic properties of sets CMSC 302. Vojislav Kecman
Introduction to Set Theory ( 2.1) VCU, Department of Computer Science CMSC 302 Sets Vojislav Kecman A set is a new type of structure, representing an unordered collection (group, plurality) of zero or
More informationFoundations Revision Notes
oundations Revision Notes hese notes are designed as an aid not a substitute for revision. A lot of proofs have not been included because you should have them in your notes, should you need them. Also,
More informationMathematics-I Prof. S.K. Ray Department of Mathematics and Statistics Indian Institute of Technology, Kanpur. Lecture 1 Real Numbers
Mathematics-I Prof. S.K. Ray Department of Mathematics and Statistics Indian Institute of Technology, Kanpur Lecture 1 Real Numbers In these lectures, we are going to study a branch of mathematics called
More informationMath 31 Lesson Plan. Day 2: Sets; Binary Operations. Elizabeth Gillaspy. September 23, 2011
Math 31 Lesson Plan Day 2: Sets; Binary Operations Elizabeth Gillaspy September 23, 2011 Supplies needed: 30 worksheets. Scratch paper? Sign in sheet Goals for myself: Tell them what you re going to tell
More informationIntroduction: Pythagorean Triplets
Introduction: Pythagorean Triplets On this first day I want to give you an idea of what sorts of things we talk about in number theory. In number theory we want to study the natural numbers, and in particular
More information3. Abstract Boolean Algebras
3. ABSTRACT BOOLEAN ALGEBRAS 123 3. Abstract Boolean Algebras 3.1. Abstract Boolean Algebra. Definition 3.1.1. An abstract Boolean algebra is defined as a set B containing two distinct elements 0 and 1,
More informationBasic counting techniques. Periklis A. Papakonstantinou Rutgers Business School
Basic counting techniques Periklis A. Papakonstantinou Rutgers Business School i LECTURE NOTES IN Elementary counting methods Periklis A. Papakonstantinou MSIS, Rutgers Business School ALL RIGHTS RESERVED
More informationSets. Slides by Christopher M. Bourke Instructor: Berthe Y. Choueiry. Fall 2007
Slides by Christopher M. Bourke Instructor: Berthe Y. Choueiry Fall 2007 1 / 42 Computer Science & Engineering 235 Introduction to Discrete Mathematics Sections 2.1, 2.2 of Rosen Introduction I Introduction
More informationSets. Slides by Christopher M. Bourke Instructor: Berthe Y. Choueiry. Spring 2006
Slides by Christopher M. Bourke Instructor: Berthe Y. Choueiry Spring 2006 1 / 1 Computer Science & Engineering 235 Introduction to Discrete Mathematics Sections 1.6 1.7 of Rosen Introduction I We ve already
More informationChapter 7. Inclusion-Exclusion a.k.a. The Sieve Formula
Chapter 7. Inclusion-Exclusion a.k.a. The Sieve Formula Prof. Tesler Math 184A Fall 2019 Prof. Tesler Ch. 7. Inclusion-Exclusion Math 184A / Fall 2019 1 / 25 Venn diagram and set sizes A = {1, 2, 3, 4,
More informationHW 4 SOLUTIONS. , x + x x 1 ) 2
HW 4 SOLUTIONS The Way of Analysis p. 98: 1.) Suppose that A is open. Show that A minus a finite set is still open. This follows by induction as long as A minus one point x is still open. To see that A
More information6 CARDINALITY OF SETS
6 CARDINALITY OF SETS MATH10111 - Foundations of Pure Mathematics We all have an idea of what it means to count a finite collection of objects, but we must be careful to define rigorously what it means
More informationBackground for Discrete Mathematics
Background for Discrete Mathematics Huck Bennett Northwestern University These notes give a terse summary of basic notation and definitions related to three topics in discrete mathematics: logic, sets,
More informationAn Introduction to Combinatorics
Chapter 1 An Introduction to Combinatorics What Is Combinatorics? Combinatorics is the study of how to count things Have you ever counted the number of games teams would play if each team played every
More informationSpring 2014 Advanced Probability Overview. Lecture Notes Set 1: Course Overview, σ-fields, and Measures
36-752 Spring 2014 Advanced Probability Overview Lecture Notes Set 1: Course Overview, σ-fields, and Measures Instructor: Jing Lei Associated reading: Sec 1.1-1.4 of Ash and Doléans-Dade; Sec 1.1 and A.1
More informationPractical Algebra. A Step-by-step Approach. Brought to you by Softmath, producers of Algebrator Software
Practical Algebra A Step-by-step Approach Brought to you by Softmath, producers of Algebrator Software 2 Algebra e-book Table of Contents Chapter 1 Algebraic expressions 5 1 Collecting... like terms 5
More information4. What is the probability that the two values differ by 4 or more in absolute value? There are only six
1. Short Questions: 2/2/2/2/2 Provide a clear and concise justification of your answer. In this problem, you roll two balanced six-sided dice. Hint: Draw a picture. 1. What is the probability that the
More informationMath 300: Foundations of Higher Mathematics Northwestern University, Lecture Notes
Math 300: Foundations of Higher Mathematics Northwestern University, Lecture Notes Written by Santiago Cañez These are notes which provide a basic summary of each lecture for Math 300, Foundations of Higher
More informationMath 541 Fall 2008 Connectivity Transition from Math 453/503 to Math 541 Ross E. Staffeldt-August 2008
Math 541 Fall 2008 Connectivity Transition from Math 453/503 to Math 541 Ross E. Staffeldt-August 2008 Closed sets We have been operating at a fundamental level at which a topological space is a set together
More informationStatistics for Financial Engineering Session 2: Basic Set Theory March 19 th, 2006
Statistics for Financial Engineering Session 2: Basic Set Theory March 19 th, 2006 Topics What is a set? Notations for sets Empty set Inclusion/containment and subsets Sample spaces and events Operations
More informationA lower bound for X is an element z F such that
Math 316, Intro to Analysis Completeness. Definition 1 (Upper bounds). Let F be an ordered field. For a subset X F an upper bound for X is an element y F such that A lower bound for X is an element z F
More information1 Chapter 1: SETS. 1.1 Describing a set
1 Chapter 1: SETS set is a collection of objects The objects of the set are called elements or members Use capital letters :, B, C, S, X, Y to denote the sets Use lower case letters to denote the elements:
More informationICS141: Discrete Mathematics for Computer Science I
ICS141: Discrete Mathematics for Computer Science I Dept. Information & Computer Sci., Jan Stelovsky based on slides by Dr. Baek and Dr. Still Originals by Dr. M. P. Frank and Dr. J.L. Gross Provided by
More informationmeans is a subset of. So we say A B for sets A and B if x A we have x B holds. BY CONTRAST, a S means that a is a member of S.
1 Notation For those unfamiliar, we have := means equal by definition, N := {0, 1,... } or {1, 2,... } depending on context. (i.e. N is the set or collection of counting numbers.) In addition, means for
More informationCIS 2033 Lecture 5, Fall
CIS 2033 Lecture 5, Fall 2016 1 Instructor: David Dobor September 13, 2016 1 Supplemental reading from Dekking s textbook: Chapter2, 3. We mentioned at the beginning of this class that calculus was a prerequisite
More informationGenerating Functions
8.30 lecture notes March, 0 Generating Functions Lecturer: Michel Goemans We are going to discuss enumeration problems, and how to solve them using a powerful tool: generating functions. What is an enumeration
More information2. Introduction to commutative rings (continued)
2. Introduction to commutative rings (continued) 2.1. New examples of commutative rings. Recall that in the first lecture we defined the notions of commutative rings and field and gave some examples of
More informationMTHSC 3190 Section 2.9 Sets a first look
MTHSC 3190 Section 2.9 Sets a first look Definition A set is a repetition free unordered collection of objects called elements. Definition A set is a repetition free unordered collection of objects called
More information2.23 Theorem. Let A and B be sets in a metric space. If A B, then L(A) L(B).
2.23 Theorem. Let A and B be sets in a metric space. If A B, then L(A) L(B). 2.24 Theorem. Let A and B be sets in a metric space. Then L(A B) = L(A) L(B). It is worth noting that you can t replace union
More informationALGEBRAIC STRUCTURE AND DEGREE REDUCTION
ALGEBRAIC STRUCTURE AND DEGREE REDUCTION Let S F n. We define deg(s) to be the minimal degree of a non-zero polynomial that vanishes on S. We have seen that for a finite set S, deg(s) n S 1/n. In fact,
More informationComplete Induction and the Well- Ordering Principle
Complete Induction and the Well- Ordering Principle Complete Induction as a Rule of Inference In mathematical proofs, complete induction (PCI) is a rule of inference of the form P (a) P (a + 1) P (b) k
More information1. Foundations of Numerics from Advanced Mathematics. Mathematical Essentials and Notation
1. Foundations of Numerics from Advanced Mathematics Mathematical Essentials and Notation Mathematical Essentials and Notation, October 22, 2012 1 The main purpose of this first chapter (about 4 lectures)
More informationDiscrete Mathematics and Probability Theory Fall 2018 Alistair Sinclair and Yun Song Note 6
CS 70 Discrete Mathematics and Probability Theory Fall 2018 Alistair Sinclair and Yun Song Note 6 1 Modular Arithmetic In several settings, such as error-correcting codes and cryptography, we sometimes
More informationProof by Contradiction
Proof by Contradiction MAT231 Transition to Higher Mathematics Fall 2014 MAT231 (Transition to Higher Math) Proof by Contradiction Fall 2014 1 / 12 Outline 1 Proving Statements with Contradiction 2 Proving
More informationFundamentals of Probability CE 311S
Fundamentals of Probability CE 311S OUTLINE Review Elementary set theory Probability fundamentals: outcomes, sample spaces, events Outline ELEMENTARY SET THEORY Basic probability concepts can be cast in
More informationP1 Chapter 3 :: Equations and Inequalities
P1 Chapter 3 :: Equations and Inequalities jfrost@tiffin.kingston.sch.uk www.drfrostmaths.com @DrFrostMaths Last modified: 26 th August 2017 Use of DrFrostMaths for practice Register for free at: www.drfrostmaths.com/homework
More information0 Logical Background. 0.1 Sets
0 Logical Background 0.1 Sets In this course we will use the term set to simply mean a collection of things which have a common property such as the totality of positive integers or the collection of points
More informationWe want to show P (n) is true for all integers
Generalized Induction Proof: Let P (n) be the proposition 1 + 2 + 2 2 + + 2 n = 2 n+1 1. We want to show P (n) is true for all integers n 0. Generalized Induction Example: Use generalized induction to
More informationWUCT121. Discrete Mathematics. Logic. Tutorial Exercises
WUCT11 Discrete Mathematics Logic Tutorial Exercises 1 Logic Predicate Logic 3 Proofs 4 Set Theory 5 Relations and Functions WUCT11 Logic Tutorial Exercises 1 Section 1: Logic Question1 For each of the
More informationDiscrete Mathematics: Lectures 6 and 7 Sets, Relations, Functions and Counting Instructor: Arijit Bishnu Date: August 4 and 6, 2009
Discrete Mathematics: Lectures 6 and 7 Sets, Relations, Functions and Counting Instructor: Arijit Bishnu Date: August 4 and 6, 2009 Our main goal is here is to do counting using functions. For that, we
More informationSection 2: Classes of Sets
Section 2: Classes of Sets Notation: If A, B are subsets of X, then A \ B denotes the set difference, A \ B = {x A : x B}. A B denotes the symmetric difference. A B = (A \ B) (B \ A) = (A B) \ (A B). Remarks
More informationGeneralized Pigeonhole Properties of Graphs and Oriented Graphs
Europ. J. Combinatorics (2002) 23, 257 274 doi:10.1006/eujc.2002.0574 Available online at http://www.idealibrary.com on Generalized Pigeonhole Properties of Graphs and Oriented Graphs ANTHONY BONATO, PETER
More information2030 LECTURES. R. Craigen. Inclusion/Exclusion and Relations
2030 LECTURES R. Craigen Inclusion/Exclusion and Relations The Principle of Inclusion-Exclusion 7 ROS enumerates the union of disjoint sets. What if sets overlap? Some 17 out of 30 students in a class
More informationMATH 2200 Final Review
MATH 00 Final Review Thomas Goller December 7, 01 1 Exam Format The final exam will consist of 8-10 proofs It will take place on Tuesday, December 11, from 10:30 AM - 1:30 PM, in the usual room Topics
More informationDivisibility = 16, = 9, = 2, = 5. (Negative!)
Divisibility 1-17-2018 You probably know that division can be defined in terms of multiplication. If m and n are integers, m divides n if n = mk for some integer k. In this section, I ll look at properties
More informationElementary Properties of the Integers
Elementary Properties of the Integers 1 1. Basis Representation Theorem (Thm 1-3) 2. Euclid s Division Lemma (Thm 2-1) 3. Greatest Common Divisor 4. Properties of Prime Numbers 5. Fundamental Theorem of
More informationSet theory background for probability
Set theory background for probability Defining sets (a very naïve approach) A set is a collection of distinct objects. The objects within a set may be arbitrary, with the order of objects within them having
More informationMarkov chains. Randomness and Computation. Markov chains. Markov processes
Markov chains Randomness and Computation or, Randomized Algorithms Mary Cryan School of Informatics University of Edinburgh Definition (Definition 7) A discrete-time stochastic process on the state space
More informationQuadratic reciprocity and the Jacobi symbol Stephen McAdam Department of Mathematics University of Texas at Austin
Quadratic reciprocity and the Jacobi symbol Stephen McAdam Department of Mathematics University of Texas at Austin mcadam@math.utexas.edu Abstract: We offer a proof of quadratic reciprocity that arises
More informationProving languages to be nonregular
Proving languages to be nonregular We already know that there exist languages A Σ that are nonregular, for any choice of an alphabet Σ. This is because there are uncountably many languages in total and
More informationCSE 20 DISCRETE MATH. Winter
CSE 20 DISCRETE MATH Winter 2017 http://cseweb.ucsd.edu/classes/wi17/cse20-ab/ Today's learning goals Evaluate which proof technique(s) is appropriate for a given proposition Direct proof Proofs by contraposition
More informationMath 127 Homework. Mary Radcliffe. Due 29 March Complete the following problems. Fully justify each response.
Math 17 Homework Mary Radcliffe Due 9 March 018 Complete the following problems Fully justify each response NOTE: due to the Spring Break, this homework set is a bit longer than is typical You only need
More informationCHAPTER 3: THE INTEGERS Z
CHAPTER 3: THE INTEGERS Z MATH 378, CSUSM. SPRING 2009. AITKEN 1. Introduction The natural numbers are designed for measuring the size of finite sets, but what if you want to compare the sizes of two sets?
More informationSets. Alice E. Fischer. CSCI 1166 Discrete Mathematics for Computing Spring, Outline Sets An Algebra on Sets Summary
An Algebra on Alice E. Fischer CSCI 1166 Discrete Mathematics for Computing Spring, 2018 Alice E. Fischer... 1/37 An Algebra on 1 Definitions and Notation Venn Diagrams 2 An Algebra on 3 Alice E. Fischer...
More informationHowever another possibility is
19. Special Domains Let R be an integral domain. Recall that an element a 0, of R is said to be prime, if the corresponding principal ideal p is prime and a is not a unit. Definition 19.1. Let a and b
More informationPRIMARY DECOMPOSITION FOR THE INTERSECTION AXIOM
PRIMARY DECOMPOSITION FOR THE INTERSECTION AXIOM ALEX FINK 1. Introduction and background Consider the discrete conditional independence model M given by {X 1 X 2 X 3, X 1 X 3 X 2 }. The intersection axiom
More information1.1.1 Algebraic Operations
1.1.1 Algebraic Operations We need to learn how our basic algebraic operations interact. When confronted with many operations, we follow the order of operations: Parentheses Exponentials Multiplication
More information2. Counting and Probability
2. Counting and Probability 2.1.1 Factorials 2.1.2 Combinatorics 2.2.1 Probability Theory 2.2.2 Probability Examples 2.1.1 Factorials Combinatorics Combinatorics is the mathematics of counting. It can
More informationThe Inclusion-Exclusion Principle
The Inclusion-Exclusion Principle Introductory Example Suppose a survey of 100 people asks if they have a cat or dog as a pet. The results are as follows: 55 answered yes for cat, 58 answered yes for dog
More informationMeasure and integration
Chapter 5 Measure and integration In calculus you have learned how to calculate the size of different kinds of sets: the length of a curve, the area of a region or a surface, the volume or mass of a solid.
More information1.4 Equivalence Relations and Partitions
24 CHAPTER 1. REVIEW 1.4 Equivalence Relations and Partitions 1.4.1 Equivalence Relations Definition 1.4.1 (Relation) A binary relation or a relation on a set S is a set R of ordered pairs. This is a very
More information1 Basic Combinatorics
1 Basic Combinatorics 1.1 Sets and sequences Sets. A set is an unordered collection of distinct objects. The objects are called elements of the set. We use braces to denote a set, for example, the set
More informationModular Arithmetic Instructor: Marizza Bailey Name:
Modular Arithmetic Instructor: Marizza Bailey Name: 1. Introduction to Modular Arithmetic If someone asks you what day it is 145 days from now, what would you answer? Would you count 145 days, or find
More informationHandout 2 (Correction of Handout 1 plus continued discussion/hw) Comments and Homework in Chapter 1
22M:132 Fall 07 J. Simon Handout 2 (Correction of Handout 1 plus continued discussion/hw) Comments and Homework in Chapter 1 Chapter 1 contains material on sets, functions, relations, and cardinality that
More informationSTA111 - Lecture 1 Welcome to STA111! 1 What is the difference between Probability and Statistics?
STA111 - Lecture 1 Welcome to STA111! Some basic information: Instructor: Víctor Peña (email: vp58@duke.edu) Course Website: http://stat.duke.edu/~vp58/sta111. 1 What is the difference between Probability
More information2 Arithmetic. 2.1 Greatest common divisors. This chapter is about properties of the integers Z = {..., 2, 1, 0, 1, 2,...}.
2 Arithmetic This chapter is about properties of the integers Z = {..., 2, 1, 0, 1, 2,...}. (See [Houston, Chapters 27 & 28]) 2.1 Greatest common divisors Definition 2.16. If a, b are integers, we say
More informationT (s, xa) = T (T (s, x), a). The language recognized by M, denoted L(M), is the set of strings accepted by M. That is,
Recall A deterministic finite automaton is a five-tuple where S is a finite set of states, M = (S, Σ, T, s 0, F ) Σ is an alphabet the input alphabet, T : S Σ S is the transition function, s 0 S is the
More informationRoth s Theorem on 3-term Arithmetic Progressions
Roth s Theorem on 3-term Arithmetic Progressions Mustazee Rahman 1 Introduction This article is a discussion about the proof of a classical theorem of Roth s regarding the existence of three term arithmetic
More informationReview of Linear Algebra
Review of Linear Algebra Throughout these notes, F denotes a field (often called the scalars in this context). 1 Definition of a vector space Definition 1.1. A F -vector space or simply a vector space
More informationLecture 2: Groups. Rajat Mittal. IIT Kanpur
Lecture 2: Groups Rajat Mittal IIT Kanpur These notes are about the first abstract mathematical structure we are going to study, groups. You are already familiar with set, which is just a collection of
More information