Fill in the blanks in the following proof by contradiction that there is no least positive real number. Proof: Suppose not. That is, suppose that there is a least positive real number x. [We must deduce (a) ] Consider the number x/2. Since x is a positive real number, x/2 is also (b) . In addition, we can deduce that x/2 < x by multiplying both sides of the inequality 1 < 2 by (c) and dividing (d) . Hence x/2 is a positive real number that is less than the least positive real number. This is a (e) [Thus the supposition is false, and so there is no least positive real number.]
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Table of Contents
1.1
Variables
1.1
Variables
1.2
The Language of Sets
1.2
The Language of Sets
1.3
The Language of Relations and Functions
1.3
The Language of Relations and Functions
2.1
Logical Form and Logical Equivalence
2.1
Logical Form and Logical Equivalence
2.2
Conditional Statements
2.2
Conditional Statements
2.3
Valid and Invalid Arguments
2.3
Valid and Invalid Arguments
2.4
Application: Digital Logic Circuits
2.4
Application: Digital Logic Circuits
2.5
Application: Number Systems and Circuits for Addition
2.5
Application: Number Systems and Circuits for Addition
3.1
Predicates and Quantified Statements I
3.2
Predicates and Quantified Statements II
3.2
Predicates and Quantified Statements II
3.3
Statements with Multiple Quantifiers
3.3
Statements with Multiple Quantifiers
3.4
Arguments with Quantified Statements
3.4
Arguments with Quantified Statements
4.1
Direct Proof and Counterexample I: Introduction
4.1
Direct Proof and Counterexample I: Introduction
4.2
Direct Proof and Counterexample II: Rational Numbers
4.2
Direct Proof and Counterexample II: Rational Numbers
4.3
Direct Proof and Counterexample III: Divisibility
4.3
Direct Proof and Counterexample III: Divisibility
4.4
Direct Proof and Counterexample IV: Division into Cases and the Quotient-Remainder Theorem
4.4
Direct Proof and Counterexample IV: Division into Cases and the Quotient-Remainder Theorem
4.5
Direct Proof and Counterexample V: Floor and Ceiling
4.5
Direct Proof and Counterexample V: Floor and Ceiling
4.6
Indirect Argument: Contradiction and Contraposition
4.6
Indirect Argument: Contradiction and Contraposition
4.7
Indirect Argument: Two Classical Theorems
4.7
Indirect Argument: Two Classical Theorems
4.8
Application: Algorithms
4.8
Application: Algorithms
5.1
Sequences
5.1
Sequences
5.2
Mathematical Induction I
5.2
Mathematical Induction I
5.3
Mathematical Induction II
5.3
Mathematical Induction II
5.4
Strong Mathematical Induction and the Well-Ordering Principle for the Integers
5.4
Strong Mathematical Induction and the Well-Ordering Principle for the Integers
5.5
Application: Correctness of Algorithms
5.5
Application: Correctness of Algorithms
5.6
Defining Sequences Recursively
5.6
Defining Sequences Recursively
5.7
Solving Recurrence Relations by Iteration
5.7
Solving Recurrence Relations by Iteration
5.8
Second-Order Linear Homogenous Recurrence Relations with Constant Coefficients
5.8
Second-Order Linear Homogenous Recurrence Relations with Constant Coefficients
5.9
General Recursive Definitions and Structural Induction
5.9
General Recursive Definitions and Structural Induction
6.1
Set Theory: Definitions and the Element Method of Proof
6.1
Set Theory: Definitions and the Element Method of Proof
6.2
Properties of Sets
6.2
Properties of Sets
6.3
Disproofs, Algebraic Proofs, and Boolean Algebras
6.3
Disproofs, Algebraic Proofs, and Boolean Algebras
6.4
Boolean Algebras, Russell’s Paradox, and the Halting Problem
6.4
Boolean Algebras, Russell’s Paradox, and the Halting Problem
7.1
Functions Defined on General Sets
7.1
Functions Defined on General Sets
7.2
One-to-One and Onto, Inverse Functions
7.2
One-to-One and Onto, Inverse Functions
7.3
Composition of Functions
7.3
Composition of Functions
7.4
Cardinality with Applications to Computability
7.4
Cardinality with Applications to Computability
8.1
Relations on Sets
8.1
Relations on Sets
8.2
Reflexivity, Symmetry, and Transitivity
8.2
Reflexivity, Symmetry, and Transitivity
8.3
Equivalence Relations
8.3
Equivalence Relations
8.4
Modular Arithmetic with Applications to Cryptography
8.4
Modular Arithmetic with Applications to Cryptography
8.5
Partial Order Relations
8.5
Partial Order Relations
9.1
Introduction
9.1
Introduction
9.2
Possibility Trees and the Multiplication Rule
9.2
Possibility Trees and the Multiplication Rule
9.3
Counting Elements of Disjoint Sets: The Addition Rule
9.3
Counting Elements of Disjoint Sets: The Addition Rule
9.4
The Pigeonhole Principle
9.4
The Pigeonhole Principle
9.5
Counting Subsets of a Set: Combinations
9.5
Counting Subsets of a Set: Combinations
9.6
r-Combinations with Repetition Allowed
9.6
r-Combinations with Repetition Allowed
9.7
Pascal’s Formula and the Binomial Theorem
9.7
Pascal’s Formula and the Binomial Theorem
9.8
Probability Axioms and Expected Value
9.8
Probability Axioms and Expected Value
9.9
Conditional Probability, Bayes’ Formula, and Independent Events
9.9
Conditional Probability, Bayes’ Formula, and Independent Events
10.1
Graphs: Definitions and Basic Properties
10.1
Graphs: Definitions and Basic Properties
10.2
Trails, Paths, and Circuits
10.2
Trails, Paths, and Circuits
10.3
Matrix Representations of Graphs
10.3
Matrix Representations of Graphs
10.4
Isomorphisms of Graphs
10.4
Isomorphisms of Graphs
10.5
Trees
10.5
Trees
10.6
Rooted Trees
10.6
Rooted Trees
10.7
Spanning Trees and Shortest Paths
10.7
Spanning Trees and Shortest Paths
11.1
Real-Valued Functions of a Real Variable and Their Graphs
11.1
Real-Valued Functions of a Real Variable and Their Graphs
11.2
Notations
11.2
Notations
11.3
Application: Analysis of Algorithm Efficiency I
11.3
Application: Analysis of Algorithm Efficiency I
11.4
Exponential and Logarithmic Functions: Graphs and Orders
11.4
Exponential and Logarithmic Functions: Graphs and Orders
11.5
Application: Analysis of Algorithm Efficiency II
11.5
Application: Analysis of Algorithm Efficiency II
12.1
Formal Languages and Regular Expressions
12.1
Formal Languages and Regular Expressions
12.2
Finite-State Automata
12.2
Finite-State Automata
12.3
Simplifying Finite-State Automata
12.3
Simplifying Finite-State Automata
Textbook Solutions for Discrete Mathematics with Applications
Chapter 4.6 Problem 2
Question
Is 1 0 an irrational number? Explain.
Solution
The first step in solving 4.6 problem number 2 trying to solve the problem we have to refer to the textbook question: Is 1 0 an irrational number? Explain.
From the textbook chapter Indirect Argument: Contradiction and Contraposition you will find a few key concepts needed to solve this.
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full solution
Title
Discrete Mathematics with Applications 4
Author
Susanna S. Epp
ISBN
9780495391326