1.1 Introduction to Sets

Size: px
Start display at page:

Download "1.1 Introduction to Sets"

Transcription

1 1.1 Introduction to Sets A set is a collection of items. These items are referred to as the elements or members of the set. We usually use upper-case letters, such as A and B, to denote sets. We can write down a set in two ways: Roster notation: Listing all the elements of the set between a pair of curly braces. example, {a, b, c, d}. For Set-builder notation: Defining the set in terms of its properties. For example, the same set {a, b, c, d} can be written as {x x is one of the first four letters in the English alphabet}. Notation Note: 1. Suppose we are given the set S = {a, b, c, d}. We write c S to mean c is an element of the set S. We write f / S to mean f is not an element of the set S. 2. If every element of a set A is also an element of another set B, we say that A is a subset of B and write A B. If A is not a subset of B, we write A B. Thus, {1, 2, 3} {1, 2, 3, 4} but {1, 2, 5} {1, 2, 3, 4} because 5 is in the first set but not in the second set. 3. If A B and there is at least one element of B that is not an element of A, then A is a proper subset of B and we write A B. 4. The empty set, witten as or {}, is the set with no elements. For example, {x x > 4 and x < 3} = The empty set is a subset of any set, i.e., A for any set A. When we use the symbols,, or, we should have sets on both sides of the symbol. For example, {c} {a, b, c} makes sense but c {a, b, c} does not. When we use the symbols or /, we should have an element on the left and a set on the right. For example, {c} {a, b, c} does not make sense but c {a, b, c} does. Example: Find all the subsets of {1, 2}. Example: Find all the subsets of {1, d, β}. Note: If a set has n elements, then the number of subsets will be 2 n. The reason for this will become clear in Chapter 2. 1

2 The universal set is the set of all elements being considered and is denoted by U. A Venn diagram is a way of visualizing sets. The universal set is represented by a rectangle and sets are represented as circles inside the universal set. U B A In the Venn diagram above, A is a subset of B, while both are subsets of U. Having set up the notation and terminology, we need to be able to perform operations on sets. We will consider three operations - complement, union, and intersection. Definitions: Given a universal set U and a set A U, the complement of A, written as A c, is the set of all elements that are contained in the universal set U but not in A, i.e., A c = {x x U, x / A} Note: The complement corresponds to negation in the previous chapter. Example: Let U = {1, 2, 3, 4, a, b, c}, A = {1, 2, a}, and B = {x x is an even number in U}. Find A c, B c, U c, and (A c ) c. Complement Rules: If U is a universal set, we must always have U c =, c = U If A is any subset of U, then (A c ) c = A. 2

3 Definition: The union of two sets A and B, written A B, is the set of all elements that belong to A or B, or to both. Thus A B = {x x A or x B or both} Note: Set union corresponds to inclusive disjunction in the previous chapter. Since we are adopting the convention of using the inclusive or, we normally drop the phrase or both, and write A B = {x x A or x B} Example: Let U = {1, 2, 3, 4, a, b, c, d}, A = {1, 2, a, b}, B = {2, 3, a, b, c}, and C = {2, 4, a, c}. Find A B, A A c, A B C, and A (B C). For set union, we have the following properties: A B = B A, A A c = U, and A B C = A (B C) = (A B) C Definition: The intersection of two sets A and B, written as A B, is the set of all elements that belong to both the set A and to the set B. Thus, A B = {x x A and x B} Note: Set intersection corresponds to conjunction in the previous chapter. Example: Let U = {1, 2, 3, 4, a, b, c, d}, A = {1, 2, a, b}, B = {2, 3, a, b, c}, C = {2, 4, a, c}, and D = {3, c, d}. Find A B, A A c, A D, (A B) C, and A (B C). 3

4 Definition: Two sets A and B are disjoint if they have no elements in common, i.e., if A B =. For set intersection, we have the following properties: A B = B A, A A c =, and A B C = (A B) C = A (B C) De Morgan Laws (A B) c = A c B c ( complement of union is intersection of complements ) (A B) c = A c B c ( complement of intersection is union of complements ) Distributive Laws A (B C) = (A B) (A C) A (B C) = (A B) (A C) Example: Find the region that represents (i) the set A c B C c, (ii) the set A (B C) c in the Venn diagram below. U A a d b e f c B g C h Example: Let U be the set of all students at Texas A&M, let F = {x x is a freshman}, and let C = {x x owns a car}. Describe the sets C c, F C c, and (F c C c ) c in words. 4

5 Example: Let U be the set of all students at Texas A&M, let M = {x x is taking a math course this semester} F = {x x plans to go to a football match this semester} C = {x x lives on campus} Use set notation to represent the following sets: (i) The set of students who live on campus and are not taking a math course this semester. (ii) The set of students living on campus who are taking a math course this semester and do not plan to go to a football match this semester. (iii) The set of students who are either not taking a math course this semester or are living on campus but do not plan to go to a football match this semester. (iv) The set of students who plan to go to a football match this semester, and either do not live on campus or are taking a math course this semester. Section 1.1 suggested homework: 1, 2, 3, 5, 7, 11, 13, 17, 21, 25, 28, 33, 37, 41, 43, 45, 49, 51 5

Math 166 - Week in Review #4. A proposition, or statement, is a declarative sentence that can be classified as either true or false, but not both.

Math 166 - Week in Review #4. A proposition, or statement, is a declarative sentence that can be classified as either true or false, but not both. Math 166 Spring 2007 c Heather Ramsey Page 1 Math 166 - Week in Review #4 Sections A.1 and A.2 - Propositions, Connectives, and Truth Tables A proposition, or statement, is a declarative sentence that

More information

Set operations and Venn Diagrams. COPYRIGHT 2006 by LAVON B. PAGE

Set operations and Venn Diagrams. COPYRIGHT 2006 by LAVON B. PAGE Set operations and Venn Diagrams Set operations and Venn diagrams! = { x x " and x " } This is the intersection of and. # = { x x " or x " } This is the union of and. n element of! belongs to both and,

More information

Lecture 1. Basic Concepts of Set Theory, Functions and Relations

Lecture 1. Basic Concepts of Set Theory, Functions and Relations September 7, 2005 p. 1 Lecture 1. Basic Concepts of Set Theory, Functions and Relations 0. Preliminaries...1 1. Basic Concepts of Set Theory...1 1.1. Sets and elements...1 1.2. Specification of sets...2

More information

THE LANGUAGE OF SETS AND SET NOTATION

THE LANGUAGE OF SETS AND SET NOTATION THE LNGGE OF SETS ND SET NOTTION Mathematics is often referred to as a language with its own vocabulary and rules of grammar; one of the basic building blocks of the language of mathematics is the language

More information

Lecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett

Lecture Note 1 Set and Probability Theory. MIT 14.30 Spring 2006 Herman Bennett Lecture Note 1 Set and Probability Theory MIT 14.30 Spring 2006 Herman Bennett 1 Set Theory 1.1 Definitions and Theorems 1. Experiment: any action or process whose outcome is subject to uncertainty. 2.

More information

Set Theory: Shading Venn Diagrams

Set Theory: Shading Venn Diagrams Set Theory: Shading Venn Diagrams Venn diagrams are representations of sets that use pictures. We will work with Venn diagrams involving two sets (two-circle diagrams) and three sets (three-circle diagrams).

More information

A Little Set Theory (Never Hurt Anybody)

A Little Set Theory (Never Hurt Anybody) A Little Set Theory (Never Hurt Anybody) Matthew Saltzman Department of Mathematical Sciences Clemson University Draft: August 21, 2013 1 Introduction The fundamental ideas of set theory and the algebra

More information

Basic Set Theory. 1. Motivation. Fido Sue. Fred Aristotle Bob. LX 502 - Semantics I September 11, 2008

Basic Set Theory. 1. Motivation. Fido Sue. Fred Aristotle Bob. LX 502 - Semantics I September 11, 2008 Basic Set Theory LX 502 - Semantics I September 11, 2008 1. Motivation When you start reading these notes, the first thing you should be asking yourselves is What is Set Theory and why is it relevant?

More information

Math/Stats 425 Introduction to Probability. 1. Uncertainty and the axioms of probability

Math/Stats 425 Introduction to Probability. 1. Uncertainty and the axioms of probability Math/Stats 425 Introduction to Probability 1. Uncertainty and the axioms of probability Processes in the real world are random if outcomes cannot be predicted with certainty. Example: coin tossing, stock

More information

Check Skills You ll Need. New Vocabulary union intersection disjoint sets. Union of Sets

Check Skills You ll Need. New Vocabulary union intersection disjoint sets. Union of Sets NY-4 nion and Intersection of Sets Learning Standards for Mathematics..31 Find the intersection of sets (no more than three sets) and/or union of sets (no more than three sets). Check Skills You ll Need

More information

Probability: Terminology and Examples Class 2, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom

Probability: Terminology and Examples Class 2, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom Probability: Terminology and Examples Class 2, 18.05, Spring 2014 Jeremy Orloff and Jonathan Bloom 1 Learning Goals 1. Know the definitions of sample space, event and probability function. 2. Be able to

More information

STAT 319 Probability and Statistics For Engineers PROBABILITY. Engineering College, Hail University, Saudi Arabia

STAT 319 Probability and Statistics For Engineers PROBABILITY. Engineering College, Hail University, Saudi Arabia STAT 319 robability and Statistics For Engineers LECTURE 03 ROAILITY Engineering College, Hail University, Saudi Arabia Overview robability is the study of random events. The probability, or chance, that

More information

1.4 Compound Inequalities

1.4 Compound Inequalities Section 1.4 Compound Inequalities 53 1.4 Compound Inequalities This section discusses a technique that is used to solve compound inequalities, which is a phrase that usually refers to a pair of inequalities

More information

Automata and Formal Languages

Automata and Formal Languages Automata and Formal Languages Winter 2009-2010 Yacov Hel-Or 1 What this course is all about This course is about mathematical models of computation We ll study different machine models (finite automata,

More information

Absolute Value Equations and Inequalities

Absolute Value Equations and Inequalities Key Concepts: Compound Inequalities Absolute Value Equations and Inequalities Intersections and unions Suppose that A and B are two sets of numbers. The intersection of A and B is the set of all numbers

More information

Chapter 1 Section 4: Compound Linear Inequalities

Chapter 1 Section 4: Compound Linear Inequalities Chapter 1 Section 4: Compound Linear Inequalities Introduction Compound linear inequalities involve finding the union or intersection of solution sets of two or more linear inequalities. You ve already

More information

SOLUTIONS TO ASSIGNMENT 1 MATH 576

SOLUTIONS TO ASSIGNMENT 1 MATH 576 SOLUTIONS TO ASSIGNMENT 1 MATH 576 SOLUTIONS BY OLIVIER MARTIN 13 #5. Let T be the topology generated by A on X. We want to show T = J B J where B is the set of all topologies J on X with A J. This amounts

More information

Access The Mathematics of Internet Search Engines

Access The Mathematics of Internet Search Engines Lesson1 Access The Mathematics of Internet Search Engines You are living in the midst of an ongoing revolution in information processing and telecommunications. Telephones, televisions, and computers are

More information

Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University

Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University Lecture 1 Introduction Properties of Probability Methods of Enumeration Asrat Temesgen Stockholm University 1 Chapter 1 Probability 1.1 Basic Concepts In the study of statistics, we consider experiments

More information

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products

Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products Chapter 3 Cartesian Products and Relations The material in this chapter is the first real encounter with abstraction. Relations are very general thing they are a special type of subset. After introducing

More information

Complement. If A is an event, then the complement of A, written A c, means all the possible outcomes that are not in A.

Complement. If A is an event, then the complement of A, written A c, means all the possible outcomes that are not in A. Complement If A is an event, then the complement of A, written A c, means all the possible outcomes that are not in A. For example, if A is the event UNC wins at least 5 football games, then A c is the

More information

Logic in Computer Science: Logic Gates

Logic in Computer Science: Logic Gates Logic in Computer Science: Logic Gates Lila Kari The University of Western Ontario Logic in Computer Science: Logic Gates CS2209, Applied Logic for Computer Science 1 / 49 Logic and bit operations Computers

More information

ACTIVITY: Identifying Common Multiples

ACTIVITY: Identifying Common Multiples 1.6 Least Common Multiple of two numbers? How can you find the least common multiple 1 ACTIVITY: Identifying Common Work with a partner. Using the first several multiples of each number, copy and complete

More information

Statistics 100A Homework 1 Solutions

Statistics 100A Homework 1 Solutions Chapter 1 tatistics 100A Homework 1 olutions Ryan Rosario 1. (a) How many different 7-place license plates are possible if the first 2 places are for letters and the other 5 for numbers? The first two

More information

INTRODUCTORY SET THEORY

INTRODUCTORY SET THEORY M.Sc. program in mathematics INTRODUCTORY SET THEORY Katalin Károlyi Department of Applied Analysis, Eötvös Loránd University H-1088 Budapest, Múzeum krt. 6-8. CONTENTS 1. SETS Set, equal sets, subset,

More information

Formal Languages and Automata Theory - Regular Expressions and Finite Automata -

Formal Languages and Automata Theory - Regular Expressions and Finite Automata - Formal Languages and Automata Theory - Regular Expressions and Finite Automata - Samarjit Chakraborty Computer Engineering and Networks Laboratory Swiss Federal Institute of Technology (ETH) Zürich March

More information

Basic Probability Concepts

Basic Probability Concepts page 1 Chapter 1 Basic Probability Concepts 1.1 Sample and Event Spaces 1.1.1 Sample Space A probabilistic (or statistical) experiment has the following characteristics: (a) the set of all possible outcomes

More information

Mathematics for Computer Science/Software Engineering. Notes for the course MSM1F3 Dr. R. A. Wilson

Mathematics for Computer Science/Software Engineering. Notes for the course MSM1F3 Dr. R. A. Wilson Mathematics for Computer Science/Software Engineering Notes for the course MSM1F3 Dr. R. A. Wilson October 1996 Chapter 1 Logic Lecture no. 1. We introduce the concept of a proposition, which is a statement

More information

Handout #1: Mathematical Reasoning

Handout #1: Mathematical Reasoning Math 101 Rumbos Spring 2010 1 Handout #1: Mathematical Reasoning 1 Propositional Logic A proposition is a mathematical statement that it is either true or false; that is, a statement whose certainty or

More information

7 Relations and Functions

7 Relations and Functions 7 Relations and Functions In this section, we introduce the concept of relations and functions. Relations A relation R from a set A to a set B is a set of ordered pairs (a, b), where a is a member of A,

More information

Discrete Mathematics

Discrete Mathematics Discrete Mathematics Chih-Wei Yi Dept. of Computer Science National Chiao Tung University March 16, 2009 2.1 Sets 2.1 Sets 2.1 Sets Basic Notations for Sets For sets, we ll use variables S, T, U,. We can

More information

Mathematical Conventions Large Print (18 point) Edition

Mathematical Conventions Large Print (18 point) Edition GRADUATE RECORD EXAMINATIONS Mathematical Conventions Large Print (18 point) Edition Copyright 2010 by Educational Testing Service. All rights reserved. ETS, the ETS logo, GRADUATE RECORD EXAMINATIONS,

More information

Course Syllabus. MATH 1350-Mathematics for Teachers I. Revision Date: 8/15/2016

Course Syllabus. MATH 1350-Mathematics for Teachers I. Revision Date: 8/15/2016 Course Syllabus MATH 1350-Mathematics for Teachers I Revision Date: 8/15/2016 Catalog Description: This course is intended to build or reinforce a foundation in fundamental mathematics concepts and skills.

More information

Mathematical Conventions. for the Quantitative Reasoning Measure of the GRE revised General Test

Mathematical Conventions. for the Quantitative Reasoning Measure of the GRE revised General Test Mathematical Conventions for the Quantitative Reasoning Measure of the GRE revised General Test www.ets.org Overview The mathematical symbols and terminology used in the Quantitative Reasoning measure

More information

Automata Theory. Şubat 2006 Tuğrul Yılmaz Ankara Üniversitesi

Automata Theory. Şubat 2006 Tuğrul Yılmaz Ankara Üniversitesi Automata Theory Automata theory is the study of abstract computing devices. A. M. Turing studied an abstract machine that had all the capabilities of today s computers. Turing s goal was to describe the

More information

Factorizations: Searching for Factor Strings

Factorizations: Searching for Factor Strings " 1 Factorizations: Searching for Factor Strings Some numbers can be written as the product of several different pairs of factors. For example, can be written as 1, 0,, 0, and. It is also possible to write

More information

Basic Concepts of Set Theory, Functions and Relations

Basic Concepts of Set Theory, Functions and Relations March 1, 2006 p. 1 Basic Concepts of Set Theory, Functions and Relations 1. Basic Concepts of Set Theory...1 1.1. Sets and elements...1 1.2. Specification of sets...2 1.3. Identity and cardinality...3

More information

Applied Liberal Arts Mathematics MAT-105-TE

Applied Liberal Arts Mathematics MAT-105-TE Applied Liberal Arts Mathematics MAT-105-TE This TECEP tests a broad-based overview of mathematics intended for non-math majors and emphasizes problem-solving modeled on real-life applications. Topics

More information

All of mathematics can be described with sets. This becomes more and

All of mathematics can be described with sets. This becomes more and CHAPTER 1 Sets All of mathematics can be described with sets. This becomes more and more apparent the deeper into mathematics you go. It will be apparent in most of your upper level courses, and certainly

More information

Sudoku puzzles and how to solve them

Sudoku puzzles and how to solve them Sudoku puzzles and how to solve them Andries E. Brouwer 2006-05-31 1 Sudoku Figure 1: Two puzzles the second one is difficult A Sudoku puzzle (of classical type ) consists of a 9-by-9 matrix partitioned

More information

6.3 Conditional Probability and Independence

6.3 Conditional Probability and Independence 222 CHAPTER 6. PROBABILITY 6.3 Conditional Probability and Independence Conditional Probability Two cubical dice each have a triangle painted on one side, a circle painted on two sides and a square painted

More information

Classifying Lesson 1 Triangles

Classifying Lesson 1 Triangles Classifying Lesson 1 acute angle congruent scalene Classifying VOCABULARY right angle isosceles Venn diagram obtuse angle equilateral You classify many things around you. For example, you might choose

More information

10.2 Series and Convergence

10.2 Series and Convergence 10.2 Series and Convergence Write sums using sigma notation Find the partial sums of series and determine convergence or divergence of infinite series Find the N th partial sums of geometric series and

More information

Sample Induction Proofs

Sample Induction Proofs Math 3 Worksheet: Induction Proofs III, Sample Proofs A.J. Hildebrand Sample Induction Proofs Below are model solutions to some of the practice problems on the induction worksheets. The solutions given

More information

Regular Languages and Finite State Machines

Regular Languages and Finite State Machines Regular Languages and Finite State Machines Plan for the Day: Mathematical preliminaries - some review One application formal definition of finite automata Examples 1 Sets A set is an unordered collection

More information

Greatest Common Factors and Least Common Multiples with Venn Diagrams

Greatest Common Factors and Least Common Multiples with Venn Diagrams Greatest Common Factors and Least Common Multiples with Venn Diagrams Stephanie Kolitsch and Louis Kolitsch The University of Tennessee at Martin Martin, TN 38238 Abstract: In this article the authors

More information

LOGIC AND SETS CLAST MATHEMATICS COMPETENCIES

LOGIC AND SETS CLAST MATHEMATICS COMPETENCIES 5 LOGIC AND SETS CLAST MATHEMATICS COMPETENCIES IE1: IIE1: IIE2: IIE3: IIE4: IIIE1: IIIE2: IVE1: Deduce facts of set inclusion or set non-inclusion from a diagram Identify statements equivalent to the

More information

Section 1.1 Real Numbers

Section 1.1 Real Numbers . Natural numbers (N):. Integer numbers (Z): Section. Real Numbers Types of Real Numbers,, 3, 4,,... 0, ±, ±, ±3, ±4, ±,... REMARK: Any natural number is an integer number, but not any integer number is

More information

Automata on Infinite Words and Trees

Automata on Infinite Words and Trees Automata on Infinite Words and Trees Course notes for the course Automata on Infinite Words and Trees given by Dr. Meghyn Bienvenu at Universität Bremen in the 2009-2010 winter semester Last modified:

More information

3 0 + 4 + 3 1 + 1 + 3 9 + 6 + 3 0 + 1 + 3 0 + 1 + 3 2 mod 10 = 4 + 3 + 1 + 27 + 6 + 1 + 1 + 6 mod 10 = 49 mod 10 = 9.

3 0 + 4 + 3 1 + 1 + 3 9 + 6 + 3 0 + 1 + 3 0 + 1 + 3 2 mod 10 = 4 + 3 + 1 + 27 + 6 + 1 + 1 + 6 mod 10 = 49 mod 10 = 9. SOLUTIONS TO HOMEWORK 2 - MATH 170, SUMMER SESSION I (2012) (1) (Exercise 11, Page 107) Which of the following is the correct UPC for Progresso minestrone soup? Show why the other numbers are not valid

More information

Licensed to: Printed in the United States of America 1 2 3 4 5 6 7 15 14 13 12 11

Licensed to: Printed in the United States of America 1 2 3 4 5 6 7 15 14 13 12 11 Licensed to: CengageBrain User This is an electronic version of the print textbook. Due to electronic rights restrictions, some third party content may be suppressed. Editorial review has deemed that any

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete

More information

Lecture Notes on Pitch-Class Set Theory. Topic 4: Inversion. John Paul Ito

Lecture Notes on Pitch-Class Set Theory. Topic 4: Inversion. John Paul Ito Lecture Notes on Pitch-Class Set Theory Topic 4: Inversion John Paul Ito Inversion We have already seen in the notes on set classes that while in tonal theory, to invert a chord is to take the lowest note

More information

I. Pointwise convergence

I. Pointwise convergence MATH 40 - NOTES Sequences of functions Pointwise and Uniform Convergence Fall 2005 Previously, we have studied sequences of real numbers. Now we discuss the topic of sequences of real valued functions.

More information

Session 6 Number Theory

Session 6 Number Theory Key Terms in This Session Session 6 Number Theory Previously Introduced counting numbers factor factor tree prime number New in This Session composite number greatest common factor least common multiple

More information

Chapter 4: Probability and Counting Rules

Chapter 4: Probability and Counting Rules Chapter 4: Probability and Counting Rules Learning Objectives Upon successful completion of Chapter 4, you will be able to: Determine sample spaces and find the probability of an event using classical

More information

Reading 13 : Finite State Automata and Regular Expressions

Reading 13 : Finite State Automata and Regular Expressions CS/Math 24: Introduction to Discrete Mathematics Fall 25 Reading 3 : Finite State Automata and Regular Expressions Instructors: Beck Hasti, Gautam Prakriya In this reading we study a mathematical model

More information

3.1. Angle Pairs. What s Your Angle? Angle Pairs. ACTIVITY 3.1 Investigative. Activity Focus Measuring angles Angle pairs

3.1. Angle Pairs. What s Your Angle? Angle Pairs. ACTIVITY 3.1 Investigative. Activity Focus Measuring angles Angle pairs SUGGESTED LEARNING STRATEGIES: Think/Pair/Share, Use Manipulatives Two rays with a common endpoint form an angle. The common endpoint is called the vertex. You can use a protractor to draw and measure

More information

Cartesian Products and Relations

Cartesian Products and Relations Cartesian Products and Relations Definition (Cartesian product) If A and B are sets, the Cartesian product of A and B is the set A B = {(a, b) :(a A) and (b B)}. The following points are worth special

More information

OA3-10 Patterns in Addition Tables

OA3-10 Patterns in Addition Tables OA3-10 Patterns in Addition Tables Pages 60 63 Standards: 3.OA.D.9 Goals: Students will identify and describe various patterns in addition tables. Prior Knowledge Required: Can add two numbers within 20

More information

Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan

Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan 6 Permutation Groups Let S be a nonempty set and M(S be the collection of all mappings from S into S. In this section,

More information

Section 6.4: Counting Subsets of a Set: Combinations

Section 6.4: Counting Subsets of a Set: Combinations Section 6.4: Counting Subsets of a Set: Combinations In section 6.2, we learnt how to count the number of r-permutations from an n-element set (recall that an r-permutation is an ordered selection of r

More information

https://williamshartunionca.springboardonline.org/ebook/book/27e8f1b87a1c4555a1212b...

https://williamshartunionca.springboardonline.org/ebook/book/27e8f1b87a1c4555a1212b... of 19 9/2/2014 12:09 PM Answers Teacher Copy Plan Pacing: 1 class period Chunking the Lesson Example A #1 Example B Example C #2 Check Your Understanding Lesson Practice Teach Bell-Ringer Activity Students

More information

CHAPTER 3. Methods of Proofs. 1. Logical Arguments and Formal Proofs

CHAPTER 3. Methods of Proofs. 1. Logical Arguments and Formal Proofs CHAPTER 3 Methods of Proofs 1. Logical Arguments and Formal Proofs 1.1. Basic Terminology. An axiom is a statement that is given to be true. A rule of inference is a logical rule that is used to deduce

More information

Probability and Statistics Vocabulary List (Definitions for Middle School Teachers)

Probability and Statistics Vocabulary List (Definitions for Middle School Teachers) Probability and Statistics Vocabulary List (Definitions for Middle School Teachers) B Bar graph a diagram representing the frequency distribution for nominal or discrete data. It consists of a sequence

More information

three Entity-Relationship Modeling chapter OVERVIEW CHAPTER

three Entity-Relationship Modeling chapter OVERVIEW CHAPTER three Entity-Relationship Modeling CHAPTER chapter OVERVIEW 3.1 Introduction 3.2 The Entity-Relationship Model 3.3 Entity 3.4 Attributes 3.5 Relationships 3.6 Degree of a Relationship 3.7 Cardinality of

More information

Building a Bridge to Academic Vocabulary in Mathematics

Building a Bridge to Academic Vocabulary in Mathematics Building a Bridge to Academic Vocabulary in Mathematics AISD Elementary Mathematics Department How Students Develop a Repertoire of Academic English in Mathematics Developed and researched by the AISD

More information

INCIDENCE-BETWEENNESS GEOMETRY

INCIDENCE-BETWEENNESS GEOMETRY INCIDENCE-BETWEENNESS GEOMETRY MATH 410, CSUSM. SPRING 2008. PROFESSOR AITKEN This document covers the geometry that can be developed with just the axioms related to incidence and betweenness. The full

More information

Question of the Day. Key Concepts. Vocabulary. Mathematical Ideas. QuestionofDay

Question of the Day. Key Concepts. Vocabulary. Mathematical Ideas. QuestionofDay QuestionofDay Question of the Day What is the probability that in a family with two children, both are boys? What is the probability that in a family with two children, both are boys, if we already know

More information

Set Theory. 2.1 Presenting Sets CHAPTER2

Set Theory. 2.1 Presenting Sets CHAPTER2 CHAPTER2 Set Theory 2.1 Presenting Sets Certain notions which we all take for granted are harder to define precisely than one might expect. In Taming the Infinite: The Story of Mathematics, Ian Stewart

More information

Book of Proof. Richard Hammack Virginia Commonwealth University

Book of Proof. Richard Hammack Virginia Commonwealth University Book of Proof Richard Hammack Virginia Commonwealth University Richard Hammack (publisher) Department of Mathematics & Applied Mathematics P.O. Box 842014 Virginia Commonwealth University Richmond, Virginia,

More information

Expression. Variable Equation Polynomial Monomial Add. Area. Volume Surface Space Length Width. Probability. Chance Random Likely Possibility Odds

Expression. Variable Equation Polynomial Monomial Add. Area. Volume Surface Space Length Width. Probability. Chance Random Likely Possibility Odds Isosceles Triangle Congruent Leg Side Expression Equation Polynomial Monomial Radical Square Root Check Times Itself Function Relation One Domain Range Area Volume Surface Space Length Width Quantitative

More information

Basic Logic Gates Richard E. Haskell

Basic Logic Gates Richard E. Haskell BASIC LOGIC GATES 1 E Basic Logic Gates Richard E. Haskell All digital systems are made from a few basic digital circuits that we call logic gates. These circuits perform the basic logic functions that

More information

Probability. Section 9. Probability. Probability of A = Number of outcomes for which A happens Total number of outcomes (sample space)

Probability. Section 9. Probability. Probability of A = Number of outcomes for which A happens Total number of outcomes (sample space) Probability Section 9 Probability Probability of A = Number of outcomes for which A happens Total number of outcomes (sample space) In this section we summarise the key issues in the basic probability

More information

Solutions to Math 51 First Exam January 29, 2015

Solutions to Math 51 First Exam January 29, 2015 Solutions to Math 5 First Exam January 29, 25. ( points) (a) Complete the following sentence: A set of vectors {v,..., v k } is defined to be linearly dependent if (2 points) there exist c,... c k R, not

More information

37 Basic Geometric Shapes and Figures

37 Basic Geometric Shapes and Figures 37 Basic Geometric Shapes and Figures In this section we discuss basic geometric shapes and figures such as points, lines, line segments, planes, angles, triangles, and quadrilaterals. The three pillars

More information

Solving Systems of Linear Equations

Solving Systems of Linear Equations LECTURE 5 Solving Systems of Linear Equations Recall that we introduced the notion of matrices as a way of standardizing the expression of systems of linear equations In today s lecture I shall show how

More information

Algebra I Notes Relations and Functions Unit 03a

Algebra I Notes Relations and Functions Unit 03a OBJECTIVES: F.IF.A.1 Understand the concept of a function and use function notation. Understand that a function from one set (called the domain) to another set (called the range) assigns to each element

More information

Mathematical Methods of Engineering Analysis

Mathematical Methods of Engineering Analysis Mathematical Methods of Engineering Analysis Erhan Çinlar Robert J. Vanderbei February 2, 2000 Contents Sets and Functions 1 1 Sets................................... 1 Subsets.............................

More information

STAT 360 Probability and Statistics. Fall 2012

STAT 360 Probability and Statistics. Fall 2012 STAT 360 Probability and Statistics Fall 2012 1) General information: Crosslisted course offered as STAT 360, MATH 360 Semester: Fall 2012, Aug 20--Dec 07 Course name: Probability and Statistics Number

More information

Introduction. The Quine-McCluskey Method Handout 5 January 21, 2016. CSEE E6861y Prof. Steven Nowick

Introduction. The Quine-McCluskey Method Handout 5 January 21, 2016. CSEE E6861y Prof. Steven Nowick CSEE E6861y Prof. Steven Nowick The Quine-McCluskey Method Handout 5 January 21, 2016 Introduction The Quine-McCluskey method is an exact algorithm which finds a minimum-cost sum-of-products implementation

More information

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 A. Miller 1. Introduction. The definitions of metric space and topological space were developed in the early 1900 s, largely

More information

Elements of probability theory

Elements of probability theory 2 Elements of probability theory Probability theory provides mathematical models for random phenomena, that is, phenomena which under repeated observations yield di erent outcomes that cannot be predicted

More information

Summary of Formulas and Concepts. Descriptive Statistics (Ch. 1-4)

Summary of Formulas and Concepts. Descriptive Statistics (Ch. 1-4) Summary of Formulas and Concepts Descriptive Statistics (Ch. 1-4) Definitions Population: The complete set of numerical information on a particular quantity in which an investigator is interested. We assume

More information

Extra Credit Assignment Lesson plan. The following assignment is optional and can be completed to receive up to 5 points on a previously taken exam.

Extra Credit Assignment Lesson plan. The following assignment is optional and can be completed to receive up to 5 points on a previously taken exam. Extra Credit Assignment Lesson plan The following assignment is optional and can be completed to receive up to 5 points on a previously taken exam. The extra credit assignment is to create a typed up lesson

More information

Grade 7/8 Math Circles Sequences and Series

Grade 7/8 Math Circles Sequences and Series Faculty of Mathematics Waterloo, Ontario N2L 3G1 Centre for Education in Mathematics and Computing Grade 7/8 Math Circles Sequences and Series November 30, 2012 What are sequences? A sequence is an ordered

More information

CPS122 Lecture: State and Activity Diagrams in UML

CPS122 Lecture: State and Activity Diagrams in UML CPS122 Lecture: State and Activity Diagrams in UML Objectives: last revised February 14, 2012 1. To show how to create and read State Diagrams 2. To introduce UML Activity Diagrams Materials: 1. Demonstration

More information

Basics of Counting. The product rule. Product rule example. 22C:19, Chapter 6 Hantao Zhang. Sample question. Total is 18 * 325 = 5850

Basics of Counting. The product rule. Product rule example. 22C:19, Chapter 6 Hantao Zhang. Sample question. Total is 18 * 325 = 5850 Basics of Counting 22C:19, Chapter 6 Hantao Zhang 1 The product rule Also called the multiplication rule If there are n 1 ways to do task 1, and n 2 ways to do task 2 Then there are n 1 n 2 ways to do

More information

Students will be able to simplify and evaluate numerical and variable expressions using appropriate properties and order of operations.

Students will be able to simplify and evaluate numerical and variable expressions using appropriate properties and order of operations. Outcome 1: (Introduction to Algebra) Skills/Content 1. Simplify numerical expressions: a). Use order of operations b). Use exponents Students will be able to simplify and evaluate numerical and variable

More information

Lecture 17 : Equivalence and Order Relations DRAFT

Lecture 17 : Equivalence and Order Relations DRAFT CS/Math 240: Introduction to Discrete Mathematics 3/31/2011 Lecture 17 : Equivalence and Order Relations Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Last lecture we introduced the notion

More information

So let us begin our quest to find the holy grail of real analysis.

So let us begin our quest to find the holy grail of real analysis. 1 Section 5.2 The Complete Ordered Field: Purpose of Section We present an axiomatic description of the real numbers as a complete ordered field. The axioms which describe the arithmetic of the real numbers

More information

17 Greatest Common Factors and Least Common Multiples

17 Greatest Common Factors and Least Common Multiples 17 Greatest Common Factors and Least Common Multiples Consider the following concrete problem: An architect is designing an elegant display room for art museum. One wall is to be covered with large square

More information

CHAPTER 2. Logic. 1. Logic Definitions. Notation: Variables are used to represent propositions. The most common variables used are p, q, and r.

CHAPTER 2. Logic. 1. Logic Definitions. Notation: Variables are used to represent propositions. The most common variables used are p, q, and r. CHAPTER 2 Logic 1. Logic Definitions 1.1. Propositions. Definition 1.1.1. A proposition is a declarative sentence that is either true (denoted either T or 1) or false (denoted either F or 0). Notation:

More information

Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan

Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan 3 Binary Operations We are used to addition and multiplication of real numbers. These operations combine two real numbers

More information

COUNTING SUBSETS OF A SET: COMBINATIONS

COUNTING SUBSETS OF A SET: COMBINATIONS COUNTING SUBSETS OF A SET: COMBINATIONS DEFINITION 1: Let n, r be nonnegative integers with r n. An r-combination of a set of n elements is a subset of r of the n elements. EXAMPLE 1: Let S {a, b, c, d}.

More information

Regular Languages and Finite Automata

Regular Languages and Finite Automata Regular Languages and Finite Automata 1 Introduction Hing Leung Department of Computer Science New Mexico State University Sep 16, 2010 In 1943, McCulloch and Pitts [4] published a pioneering work on a

More information

1. Prove that the empty set is a subset of every set.

1. Prove that the empty set is a subset of every set. 1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since

More information

Statistics 100A Homework 2 Solutions

Statistics 100A Homework 2 Solutions Statistics Homework Solutions Ryan Rosario Chapter 9. retail establishment accepts either the merican Express or the VIS credit card. total of percent of its customers carry an merican Express card, 6

More information

Lesson 4. Factors and Multiples. Objectives

Lesson 4. Factors and Multiples. Objectives Student Name: Date: Contact Person Name: Phone Number: Lesson 4 Factors and Multiples Objectives Understand what factors and multiples are Write a number as a product of its prime factors Find the greatest

More information

Regular Expressions and Automata using Haskell

Regular Expressions and Automata using Haskell Regular Expressions and Automata using Haskell Simon Thompson Computing Laboratory University of Kent at Canterbury January 2000 Contents 1 Introduction 2 2 Regular Expressions 2 3 Matching regular expressions

More information