The document discusses arguments and methods of proof in discrete mathematics. It begins by defining an argument as a series of propositions that build to a conclusion. An argument is valid if the conclusion necessarily follows from true premises. The document then provides examples of valid and invalid argument forms. It introduces truth tables to assess validity and identifies common valid argument forms like modus ponens and modus tollens. The document also discusses direct proofs, proof by cases, and other proof techniques in discrete mathematics.
The document outlines 6 rules of inference used to derive logical conclusions: 1) Conjunctive simplification, 2) Disjunctive amplification, 3) Hypothetical syllogism, 4) Disjunctive syllogism, 5) Modus ponens, and 6) Modus tollens. Each rule is symbolically represented and includes an explanation of its application using truth tables to prove the validity of the logical inferences.
This document provides an introduction to propositional logic and rules of inference. It defines an argument and valid argument forms. Examples are given to illustrate valid argument forms using propositional variables. Common rules of inference like modus ponens and disjunction introduction are explained. The resolution principle for showing validity of arguments is described. Examples are provided to demonstrate applying rules of inference to build arguments and use resolution to determine validity. The document also discusses fallacies and rules of inference for quantified statements like universal and existential instantiation and generalization.
The document discusses translating statements from English to propositional logic, including:
- Conjunction and disjunction are commutative but order matters for statements with mixed operators
- How to translate conditional statements like "if P then Q" and biconditionals like "P if and only if Q"
- Necessary and sufficient conditions and how they relate to conditionals
- Examples of translating various English language statements into propositional logic statements
CMSC 56 | Lecture 16: Equivalence of Relations & Partial Orderingallyn joy calcaben
Equivalence of Relations & Partial Ordering
CMSC 56 | Discrete Mathematical Structure for Computer Science
November 21, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
The document discusses rules of inference in logic. It begins by defining an argument as having premises and a conclusion. Several common rules of inference are then outlined, including modus ponens, modus tollens, and disjunctive syllogism. The remainder of the document works through examples of arguments and tests their validity using the rules of inference. It symbolically represents the arguments and shows the step-by-step workings to determine if the conclusions follow logically from the premises.
This document discusses rules of inference in logic proofs. It defines premises and conclusions, and introduces several common rules of inference like modus ponens, modus tollens, law of syllogism, and rule of disjunction. Examples are provided to demonstrate how each rule is used to establish the validity of arguments. The learning objectives are to prove the validity of arguments using rules of inference. Additional rules of inference are also outlined.
1) The document discusses normal subgroups, providing examples and theorems about their properties.
2) A subgroup H of a group G is normal if aH=Ha for all a in G. Some key results are that subgroups of abelian groups and subgroups of index 2 are always normal.
3) The document provides examples of normal subgroups, such as the special linear group SLn,R being normal in the general linear group GLn,R. It also gives a counterexample to show not all groups where every subgroup is normal must be abelian.
This document presents an introduction to rules of inference. It defines an argument and valid argument. It then explains several common rules of inference like modus ponens, modus tollens, addition, and simplification. Modus ponens and modus tollens are based on tautologies that make the conclusions logically follow from the premises. It also discusses two common fallacies - affirming the conclusion and denying the hypothesis - which are not valid rules of inference because they are not based on tautologies. Examples are provided to illustrate each rule of inference and fallacy.
The document outlines 6 rules of inference used to derive logical conclusions: 1) Conjunctive simplification, 2) Disjunctive amplification, 3) Hypothetical syllogism, 4) Disjunctive syllogism, 5) Modus ponens, and 6) Modus tollens. Each rule is symbolically represented and includes an explanation of its application using truth tables to prove the validity of the logical inferences.
This document provides an introduction to propositional logic and rules of inference. It defines an argument and valid argument forms. Examples are given to illustrate valid argument forms using propositional variables. Common rules of inference like modus ponens and disjunction introduction are explained. The resolution principle for showing validity of arguments is described. Examples are provided to demonstrate applying rules of inference to build arguments and use resolution to determine validity. The document also discusses fallacies and rules of inference for quantified statements like universal and existential instantiation and generalization.
The document discusses translating statements from English to propositional logic, including:
- Conjunction and disjunction are commutative but order matters for statements with mixed operators
- How to translate conditional statements like "if P then Q" and biconditionals like "P if and only if Q"
- Necessary and sufficient conditions and how they relate to conditionals
- Examples of translating various English language statements into propositional logic statements
CMSC 56 | Lecture 16: Equivalence of Relations & Partial Orderingallyn joy calcaben
Equivalence of Relations & Partial Ordering
CMSC 56 | Discrete Mathematical Structure for Computer Science
November 21, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
The document discusses rules of inference in logic. It begins by defining an argument as having premises and a conclusion. Several common rules of inference are then outlined, including modus ponens, modus tollens, and disjunctive syllogism. The remainder of the document works through examples of arguments and tests their validity using the rules of inference. It symbolically represents the arguments and shows the step-by-step workings to determine if the conclusions follow logically from the premises.
This document discusses rules of inference in logic proofs. It defines premises and conclusions, and introduces several common rules of inference like modus ponens, modus tollens, law of syllogism, and rule of disjunction. Examples are provided to demonstrate how each rule is used to establish the validity of arguments. The learning objectives are to prove the validity of arguments using rules of inference. Additional rules of inference are also outlined.
1) The document discusses normal subgroups, providing examples and theorems about their properties.
2) A subgroup H of a group G is normal if aH=Ha for all a in G. Some key results are that subgroups of abelian groups and subgroups of index 2 are always normal.
3) The document provides examples of normal subgroups, such as the special linear group SLn,R being normal in the general linear group GLn,R. It also gives a counterexample to show not all groups where every subgroup is normal must be abelian.
This document presents an introduction to rules of inference. It defines an argument and valid argument. It then explains several common rules of inference like modus ponens, modus tollens, addition, and simplification. Modus ponens and modus tollens are based on tautologies that make the conclusions logically follow from the premises. It also discusses two common fallacies - affirming the conclusion and denying the hypothesis - which are not valid rules of inference because they are not based on tautologies. Examples are provided to illustrate each rule of inference and fallacy.
Discrete mathematics Ch2 Propositional Logic_Dr.khaled.Bakro د. خالد بكروDr. Khaled Bakro
Discrete Mathematics chapter 2 covers propositional logic. A proposition is a statement that is either true or false. Propositional logic uses propositional variables and logical operators like negation, conjunction, disjunction, implication and biconditional. Truth tables are used to determine the truth value of compound propositions formed using these operators. Logical equivalences between compound propositions can be shown using truth tables or by applying equivalence rules.
This document discusses predicates and quantifiers in predicate logic. It begins by explaining the limitations of propositional logic in expressing statements involving variables and relationships between objects. It then introduces predicates as statements involving variables, and quantifiers like universal ("for all") and existential ("there exists") to express the extent to which a predicate is true. Examples are provided to demonstrate how predicates and quantifiers can be used to represent statements and enable logical reasoning. The document also covers translating statements between natural language and predicate logic, and negating quantified statements.
The document provides an overview of propositional logic including:
1. It defines statements, logical connectives, and truth tables. Logical connectives like negation, conjunction, disjunction and others are explained.
2. It discusses various logical concepts like tautology, contradiction, contingency, logical equivalence, and logical implications.
3. It outlines propositional logic rules and properties including commutative, associative, distributive, De Morgan's laws, identity law, idempotent law, and transitive rule.
4. It provides an example of using truth tables to test the validity of an argument about bachelors dying young.
1) The document uses mathematical induction to prove several formulas.
2) It demonstrates proofs for formulas like 1 + 3 + 5 + ... + (2n-1) = n^2 and 2 + 4 + ... + 2n = n(n+1).
3) The proofs follow the standard structure of mathematical induction, showing the base case is true and using the induction hypothesis to show if the statement is true for n it is also true for n+1.
This document discusses proof by contradiction, an indirect proof method. It provides examples of using proof by contradiction to prove different mathematical statements. The key steps in a proof by contradiction are: 1) assume the statement to be proved is false, 2) show that this assumption leads to a logical contradiction, and 3) conclude that the original statement must be true since the assumption was false. The document provides examples of proofs by contradiction for statements such as "there is no greatest integer" and "if n is an integer and n3 + 5 is odd, then n is even."
Normal subgroups are subgroups where conjugation does not affect membership. A subgroup N of a group G is normal if gng-1 is in N for all g in G and n in N. A subgroup N is normal if and only if every left coset of N is also a right coset of N. If every left coset equals a right coset, then conjugation preserves membership in N, making N a normal subgroup.
A lattice is a partially ordered set where every pair of elements has a supremum (least upper bound) and infimum (greatest lower bound). A lattice must satisfy the properties that (1) any two elements have a supremum and infimum and (2) the supremum of two elements is their join and the infimum is their meet. Common examples of lattices include the natural numbers under the divisibility relation and sets under the subset relation. Lattice theory has applications in many areas of computer science and engineering such as distributed computing, concurrency theory, and programming language semantics.
The Foundations: Logic and Proofs: Propositional Logic, Applications of Propositional Logic, Propositional Equivalence, Predicates and Quantifiers, Nested Quantifiers, Rules of Inference, Introduction to Proofs, Proof Methods and Strategy.
This document discusses ring homomorphisms, isomorphisms, and related concepts:
1) It defines a ring homomorphism as a mapping between two rings that preserves addition and multiplication.
2) An isomorphism is a ring homomorphism that is both one-to-one and onto.
3) The kernel of a ring homomorphism is the set of elements that map to the additive identity; a homomorphism is one-to-one if and only if its kernel is the singleton set containing only the additive identity.
Mathematical induction is a method of proof that can be used to prove that a statement is true for all positive integers. It involves two steps: 1) proving the statement is true for the base case, usually n = 1, and 2) assuming the statement is true for an integer k and using this to prove the statement is true for k + 1. Examples are provided to demonstrate how to use mathematical induction to prove statements such as the sum of the first n positive integers equalling n(n+1)/2 and that 7n - 1 is divisible by 6 for all positive integers n.
The document discusses the principle of mathematical induction and how it can be used to prove statements about natural numbers. It provides examples of using induction to prove statements about sums, products, and divisibility. The principle of induction states that to prove a statement P(n) is true for all natural numbers n, one must show that P(1) is true and that if P(k) is true, then P(k+1) is also true. The document provides examples of direct proofs of P(1) and inductive proofs of P(k+1) to demonstrate applications of the principle.
Cauchy's integral theorem, Cauchy's integral formula, Cauchy's integral formula for derivatives, Taylor's Series, Maclaurin’s Series,Laurent's Series,Singularities and zeros, Cauchy's Residue theorem,Evaluation various types of complex integrals.
The document discusses conditional and biconditional statements in logic. It defines conditional statements using "if...then" and biconditional statements using "if and only if". It also discusses the converse, inverse, and contrapositive of conditional statements and how their truth values relate using truth tables. Specifically, the contrapositive of a conditional statement always has the same truth value as the original conditional statement.
This document discusses logic and truth tables which are used in mathematics and computer science. It defines primitive statements, logical connectives like conjunction, disjunction, negation, implication and biconditional. Truth tables are used to determine the truth values of compound statements formed using these connectives. Examples are given to show how compound statements can be written symbolically and their truth values determined from truth tables. Decision structures like if-then and if-then-else used in programming languages are also discussed.
Discrete Mathematics is a branch of mathematics involving discrete elements that uses algebra and arithmetic. It is increasingly being applied in the practical fields of mathematics and computer science. It is a very good tool for improving reasoning and problem-solving capabilities.
The document discusses truth tables and logical connectives such as conjunction, disjunction, negation, implication and biconditionals. It provides examples of truth tables for compound propositions involving multiple variables. De Morgan's laws are explained, which state that the negation of a conjunction is the disjunction of the negations, and the negation of a disjunction is the conjunction of the negations. The concepts of tautologies, contradictions and logical equivalence are also covered.
Basic Concept of discrete math. I discuss a few topic of basic discrete math. I think you get a clear concept. Topics are definition,story of discrete math, Importance of discrete math, and many other basic topic.
The document discusses different types of relations, including reflexive, symmetric, transitive, and equivalence relations. It provides examples of each type of relation and defines their key properties. Inverse relations are also discussed, where the ordered pairs of a relation R are reversed to form the inverse relation R-1. An example demonstrates finding the domain, range, and inverse of a given relation defined by an equation.
The document defines sets, functions, and groups in mathematics. It provides examples and notation for sets, as well as definitions of subsets, proper subsets, and the empty set. Functions are defined as relations between inputs and outputs, and examples of functions are given. Groups are defined as sets with binary operations that satisfy closure, associativity, identity, and inverse properties. Examples of groups and subgroups are provided, along with Lagrange's theorem about the orders of groups and subgroups. Normal subgroups are introduced as subgroups whose left and right cosets are equal.
This section discusses applications of propositional logic, including translating English sentences to propositional logic, system specifications, and logic puzzles. It provides an example of translating the English sentence "You can access the Internet from campus only if you are a computer science major or you are not a freshman" to the propositional logic statement a→(c ∨ ¬f). It also gives an example of expressing the system specification "The automated reply cannot be sent when the file system is full" in propositional logic as p → ¬q.
- The document summarizes key concepts in propositional logic, including simple and compound propositions, logical operators like negation, conjunction, disjunction, implication, equivalence, and truth tables.
- It introduces important logical equivalences like De Morgan's laws, distribution, absorption, double negation, and equivalences involving implications. These equivalences allow proving that two propositions are logically equivalent without constructing a full truth table.
Discrete mathematics Ch2 Propositional Logic_Dr.khaled.Bakro د. خالد بكروDr. Khaled Bakro
Discrete Mathematics chapter 2 covers propositional logic. A proposition is a statement that is either true or false. Propositional logic uses propositional variables and logical operators like negation, conjunction, disjunction, implication and biconditional. Truth tables are used to determine the truth value of compound propositions formed using these operators. Logical equivalences between compound propositions can be shown using truth tables or by applying equivalence rules.
This document discusses predicates and quantifiers in predicate logic. It begins by explaining the limitations of propositional logic in expressing statements involving variables and relationships between objects. It then introduces predicates as statements involving variables, and quantifiers like universal ("for all") and existential ("there exists") to express the extent to which a predicate is true. Examples are provided to demonstrate how predicates and quantifiers can be used to represent statements and enable logical reasoning. The document also covers translating statements between natural language and predicate logic, and negating quantified statements.
The document provides an overview of propositional logic including:
1. It defines statements, logical connectives, and truth tables. Logical connectives like negation, conjunction, disjunction and others are explained.
2. It discusses various logical concepts like tautology, contradiction, contingency, logical equivalence, and logical implications.
3. It outlines propositional logic rules and properties including commutative, associative, distributive, De Morgan's laws, identity law, idempotent law, and transitive rule.
4. It provides an example of using truth tables to test the validity of an argument about bachelors dying young.
1) The document uses mathematical induction to prove several formulas.
2) It demonstrates proofs for formulas like 1 + 3 + 5 + ... + (2n-1) = n^2 and 2 + 4 + ... + 2n = n(n+1).
3) The proofs follow the standard structure of mathematical induction, showing the base case is true and using the induction hypothesis to show if the statement is true for n it is also true for n+1.
This document discusses proof by contradiction, an indirect proof method. It provides examples of using proof by contradiction to prove different mathematical statements. The key steps in a proof by contradiction are: 1) assume the statement to be proved is false, 2) show that this assumption leads to a logical contradiction, and 3) conclude that the original statement must be true since the assumption was false. The document provides examples of proofs by contradiction for statements such as "there is no greatest integer" and "if n is an integer and n3 + 5 is odd, then n is even."
Normal subgroups are subgroups where conjugation does not affect membership. A subgroup N of a group G is normal if gng-1 is in N for all g in G and n in N. A subgroup N is normal if and only if every left coset of N is also a right coset of N. If every left coset equals a right coset, then conjugation preserves membership in N, making N a normal subgroup.
A lattice is a partially ordered set where every pair of elements has a supremum (least upper bound) and infimum (greatest lower bound). A lattice must satisfy the properties that (1) any two elements have a supremum and infimum and (2) the supremum of two elements is their join and the infimum is their meet. Common examples of lattices include the natural numbers under the divisibility relation and sets under the subset relation. Lattice theory has applications in many areas of computer science and engineering such as distributed computing, concurrency theory, and programming language semantics.
The Foundations: Logic and Proofs: Propositional Logic, Applications of Propositional Logic, Propositional Equivalence, Predicates and Quantifiers, Nested Quantifiers, Rules of Inference, Introduction to Proofs, Proof Methods and Strategy.
This document discusses ring homomorphisms, isomorphisms, and related concepts:
1) It defines a ring homomorphism as a mapping between two rings that preserves addition and multiplication.
2) An isomorphism is a ring homomorphism that is both one-to-one and onto.
3) The kernel of a ring homomorphism is the set of elements that map to the additive identity; a homomorphism is one-to-one if and only if its kernel is the singleton set containing only the additive identity.
Mathematical induction is a method of proof that can be used to prove that a statement is true for all positive integers. It involves two steps: 1) proving the statement is true for the base case, usually n = 1, and 2) assuming the statement is true for an integer k and using this to prove the statement is true for k + 1. Examples are provided to demonstrate how to use mathematical induction to prove statements such as the sum of the first n positive integers equalling n(n+1)/2 and that 7n - 1 is divisible by 6 for all positive integers n.
The document discusses the principle of mathematical induction and how it can be used to prove statements about natural numbers. It provides examples of using induction to prove statements about sums, products, and divisibility. The principle of induction states that to prove a statement P(n) is true for all natural numbers n, one must show that P(1) is true and that if P(k) is true, then P(k+1) is also true. The document provides examples of direct proofs of P(1) and inductive proofs of P(k+1) to demonstrate applications of the principle.
Cauchy's integral theorem, Cauchy's integral formula, Cauchy's integral formula for derivatives, Taylor's Series, Maclaurin’s Series,Laurent's Series,Singularities and zeros, Cauchy's Residue theorem,Evaluation various types of complex integrals.
The document discusses conditional and biconditional statements in logic. It defines conditional statements using "if...then" and biconditional statements using "if and only if". It also discusses the converse, inverse, and contrapositive of conditional statements and how their truth values relate using truth tables. Specifically, the contrapositive of a conditional statement always has the same truth value as the original conditional statement.
This document discusses logic and truth tables which are used in mathematics and computer science. It defines primitive statements, logical connectives like conjunction, disjunction, negation, implication and biconditional. Truth tables are used to determine the truth values of compound statements formed using these connectives. Examples are given to show how compound statements can be written symbolically and their truth values determined from truth tables. Decision structures like if-then and if-then-else used in programming languages are also discussed.
Discrete Mathematics is a branch of mathematics involving discrete elements that uses algebra and arithmetic. It is increasingly being applied in the practical fields of mathematics and computer science. It is a very good tool for improving reasoning and problem-solving capabilities.
The document discusses truth tables and logical connectives such as conjunction, disjunction, negation, implication and biconditionals. It provides examples of truth tables for compound propositions involving multiple variables. De Morgan's laws are explained, which state that the negation of a conjunction is the disjunction of the negations, and the negation of a disjunction is the conjunction of the negations. The concepts of tautologies, contradictions and logical equivalence are also covered.
Basic Concept of discrete math. I discuss a few topic of basic discrete math. I think you get a clear concept. Topics are definition,story of discrete math, Importance of discrete math, and many other basic topic.
The document discusses different types of relations, including reflexive, symmetric, transitive, and equivalence relations. It provides examples of each type of relation and defines their key properties. Inverse relations are also discussed, where the ordered pairs of a relation R are reversed to form the inverse relation R-1. An example demonstrates finding the domain, range, and inverse of a given relation defined by an equation.
The document defines sets, functions, and groups in mathematics. It provides examples and notation for sets, as well as definitions of subsets, proper subsets, and the empty set. Functions are defined as relations between inputs and outputs, and examples of functions are given. Groups are defined as sets with binary operations that satisfy closure, associativity, identity, and inverse properties. Examples of groups and subgroups are provided, along with Lagrange's theorem about the orders of groups and subgroups. Normal subgroups are introduced as subgroups whose left and right cosets are equal.
This section discusses applications of propositional logic, including translating English sentences to propositional logic, system specifications, and logic puzzles. It provides an example of translating the English sentence "You can access the Internet from campus only if you are a computer science major or you are not a freshman" to the propositional logic statement a→(c ∨ ¬f). It also gives an example of expressing the system specification "The automated reply cannot be sent when the file system is full" in propositional logic as p → ¬q.
- The document summarizes key concepts in propositional logic, including simple and compound propositions, logical operators like negation, conjunction, disjunction, implication, equivalence, and truth tables.
- It introduces important logical equivalences like De Morgan's laws, distribution, absorption, double negation, and equivalences involving implications. These equivalences allow proving that two propositions are logically equivalent without constructing a full truth table.
This document summarizes Chapter 1, Part I of a textbook on propositional logic. It introduces key concepts in propositional logic, including propositions, logical connectives like negation, conjunction, disjunction, implication, biconditional, and truth tables. It provides examples of applying propositional logic to represent English sentences, system specifications, logic puzzles and logic circuits. It also briefly describes representing knowledge about an electrical system in propositional logic for fault diagnosis in artificial intelligence.
This document introduces basic concepts in propositional logic, including:
1. Propositions are declarative statements that are either true or false. Compound propositions consist of simple propositions connected by logical operators like AND and OR.
2. Truth tables define logical connectives like conjunction, disjunction, conditional, biconditional, and negation. Equivalences between statements can be shown through truth tables.
3. Logical implications can be proven without truth tables by showing that if the antecedent is true, the consequent must also be true. Dual statements and De Morgan's laws are also introduced.
The document discusses deductive and inductive arguments. It provides examples of valid and invalid deductive arguments using categorical propositions and conditional premises. It also discusses inductive arguments, noting that inductive conclusions generalize from specific premises rather than necessarily following from them. The document then compares deductive and inductive arguments and discusses their uses in everyday life and mathematics. It concludes by introducing some common rules of inference for deductive arguments.
The document discusses tautologies and contingency tables. It provides examples of a tautology and how a contingency table classifies subjects by two variables into cells. It also defines arguments and their validity, listing several common rules of inference like modus ponens, modus tollens, disjunctive syllogism. Examples are given of representing arguments symbolically and determining their validity. Indirect proofs via contradiction are defined as assuming the negation of the conclusion and deriving the negation of a premise, resulting in a contradiction.
UGC NET Computer Science & Application book.pdf [Sample]DIwakar Rajput
This document provides an overview of propositional logic and logical connectives. It defines key terms like proposition, logical connectives, truth tables, and normal forms. It describes the five basic logical connectives - negation, conjunction, disjunction, conditional, and bi-conditional. It provides truth tables and examples to explain each connective. It also discusses logical equivalences, precedence of operators, logic and bit operations, tautologies/contradictions, and normal forms. The document is a lesson on propositional logic from Diwakar Education Hub that covers basic concepts and terminology.
rules of inference in discrete structuresZenLooper
The document discusses rules of inference in propositional logic. It defines rules of inference as templates for valid arguments that can be used to construct more complex arguments. Several common rules are described, including modus ponens, modus tollens, hypothetical syllogism, disjunctive syllogism, and resolution. Examples are provided to demonstrate how each rule works and how multiple rules can be combined to determine the validity of arguments with multiple premises.
The document discusses key concepts in logic including propositions, truth tables, logical connectives like conjunction and disjunction, quantifiers, and valid arguments. Some key points:
- A proposition is a statement that is either true or false.
- Truth tables define the truth values of logical connectives and conditionals.
- Quantifiers like "all" and "some" are used to make generalized statements about sets.
- Venn diagrams can represent relationships between sets graphically.
- An argument is valid if the premises necessarily make the conclusion true.
This document provides an overview of propositional logic including:
- The basic components of propositional logic like propositions, connectives, truth tables
- Applications such as translating English sentences to logic, system specifications, puzzles
- Logical equivalences and showing equivalence through truth tables
- Sections cover propositions, connectives, truth tables, and applications including translation, specifications, puzzles
The document discusses propositional logic, including:
- The basic components of propositional logic like propositions, connectives, truth tables, and logical equivalences
- Applications such as translating English sentences to propositional logic, system specifications, logic puzzles
- Representing logical relationships using truth tables and showing logical equivalences
- Using propositional logic to represent an electrical system and diagnose faults
The document discusses propositional logic and truth tables. It defines statements as sentences that are either true or false. Examples of statements and non-statements are provided. The main logical connectives - and, or, if-then, if and only if, negation - are explained along with their symbols. Examples are given to illustrate how to determine the truth value of statements using truth tables for connectives involving two or more statements. The concepts of equivalent statements, tautologies, and using contradiction to check for tautologies are also explained with examples.
Laws of Logic in Discrete Structures and their applicationsZenLooper
The document discusses laws of logic and logical equivalences. It provides examples of applying logical laws such as DeMorgan's law, double negative law, and distributive law to simplify logical statements. Conditional statements are introduced and their truth tables are shown. Different logical equivalences involving implications are proven using truth tables. The inverse, converse, and contrapositive of conditional statements are defined and examples are given.
The document discusses the basics of logic including propositions, truth tables, and logical connectives. It defines a proposition as a statement that is either true or false. Compound propositions can be formed using logical connectives like AND, OR, XOR, NAND, and NOR. Truth tables are used to determine the truth value of compound propositions based on the truth values of the individual propositions. Several examples are provided to illustrate how to construct truth tables for statements using various logical connectives. One example shows that p ∧ q is equal to q ∧ p through a truth table.
This document discusses propositional logic and inference theory. It begins by defining propositions, truth values, and logical operators like conjunction, disjunction, negation, implication, biconditional, and their truth tables. It then discusses tautologies, contradictions, and logical equivalences. The document introduces rules of inference and methods for formal proof, including truth table technique and direct/indirect proofs. It provides examples of applying rules of inference and truth tables to evaluate arguments. The document outlines key concepts in propositional logic and inference theory.
The document covers key concepts in symbolic logic such as logical operations, truth tables, tautologies, valid and invalid arguments, and special valid argument forms. Logical equivalence and valid argument forms like modus ponens, modus tollens, disjunctive syllogism and hypothetical syllogism are explained. Examples are provided to illustrate logical statements, truth tables, and how to determine if an argument is valid or invalid.
The document discusses propositional logic including:
- Propositional logic uses propositions that can be either true or false and logical connectives to connect propositions.
- It introduces syntax of propositional logic including atomic and compound propositions.
- Logical connectives like negation, conjunction, disjunction, implication, and biconditional are explained along with their truth tables and significance.
- Other concepts discussed include precedence of connectives, logical equivalence, properties of operators, and limitations of propositional logic.
- Examples are provided to illustrate propositional logic concepts like truth tables, logical equivalence, and translating English statements to symbolic form.
This document outlines the key topics and concepts that will be covered in a discrete mathematics course, including logic, sets, functions, integers, sequences, counting, probability, relations, graphs, and Boolean algebra. It provides the instructor's contact information and lecture schedule. It also gives an overview of discrete mathematics and its applications in computer science. Sample problems are presented to illustrate logical connectives like negation, conjunction, disjunction, implication, biconditional, and their truth tables.
The document discusses mathematical reasoning and proofs. It provides definitions for key terminology used in proofs such as axioms, theorems, lemmas, and conjectures. It also explains rules of inference like modus ponens and rules for quantified statements. Examples are given to illustrate valid and invalid arguments as well as direct and indirect proofs of theorems.
This document outlines the objectives, schedule, curriculum and scheme of work for an English language course. The objectives are to improve speaking fluency, comprehension, vocabulary and attempt a CEFRL language test. The course will be held on Sundays from 4-5pm via YouTube live, Winksite and Blogger. The curriculum will cover topics like the alphabet, language structure, parts of speech, vocabulary, sentences and comprehension, with a focus on practice.
This is the introductory set of slides for the Basic English course.Robert Geofroy
This document outlines the objectives, schedule, curriculum and scheme of work for an English language course. The objectives are to improve speaking fluency, comprehension, enlarge vocabulary, and attempt a level test. The course will be held on Sundays from 4-5pm via YouTube live, Winksite and Blogger. The curriculum will cover topics like the alphabet, language structure, parts of speech, vocabulary, sentences and comprehension, with a focus on practice.
Sampling Distribution of Sample proportionRobert Geofroy
This document discusses sampling distributions of sample proportions. It provides examples of how to calculate the probability that a sample proportion will fall within a certain range of the true population proportion.
In one example, a candidate claims 53% of students support her candidacy. The document calculates the probability that a random sample of 400 students will show less than 49% support as 5.48%.
Another example calculates the probability that a candidate with actual 80% support will receive over 50% in a sample of 100 students as 77.34%, indicating a good chance of meeting the majority requirement.
The document discusses binary operations on sets. It provides examples of multiplication and addition operations on the set of integers Z. It introduces the concept of a Cayley table to represent a binary operation on a finite set using a table. The identity element and inverses are discussed. It is noted that the inverse of an element, if it exists, is unique. Examples are provided to check if binary operations are closed, commutative, associative, and have identities and inverses.
This document provides an overview of set theory including definitions of key terms and concepts. It defines a set as a well-defined collection of objects or elements. It discusses set operations like union, intersection, difference, and Cartesian product. It defines countable and uncountable sets and proves results like Cantor's theorem, which states that the cardinality of a power set is greater than the original set. Formal proofs involving sets are also covered.
The document discusses permutations and the symmetric group S3. It defines what a permutation is and introduces the six permutations that make up S3: the identity E, a 120 degree rotation R, a 240 degree rotation R2, a vertical reflection V, and reflections RV and R2V. It explains that S3 forms a group under composition of permutations. It also introduces the alternating group A3, which is the subgroup of S3 made up of the even permutations E, R, and R2.
The document discusses creating and manipulating datasets in Mathematica notebooks. It provides examples of creating simple numeric and associative datasets and demonstrates how to add additional rows and columns. The final section lists five datasets for the reader to construct in a notebook saved in their Wolfram Cloud project.
This document discusses Boolean algebra and logic gates. It begins with an introduction to binary logic and Boolean variables that can take on values of 0 or 1. It describes logical operators like AND, OR, and NOT. Boolean algebra provides a mathematical system for specifying and transforming logic functions. The document provides examples of Boolean functions and logic gates. It discusses topics like Boolean variables and values, Boolean functions, logical operators, Boolean arithmetic, theorems, and algebraic proofs. George Boole is credited with developing Boolean algebra. Truth tables and Karnaugh maps are shown as ways to analyze Boolean functions.
This document provides instructions and materials for a course project on solving problems using computer programming. It includes two problems - counting prime numbers below 10,000 and counting triangular numbers below 1,000,000. Algorithms are presented for both problems using pseudocode. Students are instructed to implement the algorithms in Scratch or another programming language. Sample Scratch and Python programs are included, along with testing to validate the outputs against known results. The document aims to help students learn programming skills through solving mathematical problems.
The course project involves solving two counting problems using a computer program. Problem 1 asks students to write a program to count the number of positive integer solutions to an equation with multiple variables summing to a given total. Problem 2 uses the principle of inclusion-exclusion to count the number of integers below a threshold that are not divisible by three given numbers. Students are provided templates to guide their programming solutions and are asked to test their programs on sample cases.
Using sage maths to solve systems of linear equationsRobert Geofroy
SageMathCloud is a free, open-source software for collaborative mathematical computation in areas like algebra, geometry, and number theory. It allows users to create online projects to solve systems of linear equations. For example, the document shows how the system "3x - y = 2" and "x + y = -6" can be represented using matrices in SageMathCloud, which provides the solution of x = -1 and y = -5, matching the manual solution. SageMathCloud thus provides an easy way to represent and solve systems of linear equations online.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
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This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
3. What is an Argument?
An argument is a series of propositions or
statements that end with a conclusion.These
propositions, also called hypotheses or
premises, if true, build inevitably and
necessarily to the stated conclusion.
When the conditions are satisfied, we have
what is called a valid (deductive) argument.
4. Consider…
If there is cream, then I will drink
coffee. If there is a donut, then I will
drink coffee.There is no cream and
there is a donut.
Therefore, I drink coffee.
5. Again…
If there is cream, then I will drink
coffee.
If there is a donut, then I will drink
coffee.
There is no cream and there is a donut.
Therefore, I drink coffee.
6. Formulating the Argument
• Premises
• If there is cream, then I will drink coffee.
• If there is a donut, then I will drink coffee,
• There is no cream and there is a donut.
• Conclusion
• I will drink coffee
7. Symbolically, we have…
• Premises
• If p [there is cream], then q [I will drink coffee].
• If r [there is a donut], then q [I will drink coffee],
• ~p [There is no cream] and r [there is a donut].
• Conclusion
• q [I will drink coffee].
and the argument format is:
p → q
r → q
~p ∧ r
--------
q
p: there is cream
q: I will drink coffee
r: there is a donut
8. Analysing the argument with aTruthTable
p q r p → q r → q ~p ~p ∧ r (p → q) ∧ (r → q) ∧ (~p ∧ r) ANDED → q
F F F T T T F F T
F F T
F T F
9. Valid Argument
A valid argument is an argument
where, if the premises are true,
then the conclusion must be
true.
A form of argument which is not
valid is called a fallacy.
10. Operational method ofValidation of an Argument
Form a truth table in which the premises
are columns and the conclusion is the last
column.
Star every row in which the premises are
true.
Declare the argument valid if every starred
row has aT in the last column.
Once we have verified an argument, we never
have to question its validity again.
11. Analysing the argument with aTruthTable
p q r p → q r → q ~p ~p ∧ r (p → q) ∧ (r → q) ∧ (~p ∧ r) ANDED → q
F F F T T T F F T
F F T T F T T F T
F T F T T T F F T
F T T T T T T T T
T F F F T F F F T
T F T F F F F F T
T T F T T F F F T
T T T T T F F F T
This is a valid argument.
12. Consider the argument…
If you have a valid password, then you
can log on to the network.You have a
valid password.
You can log on to the network.
13. Consider the argument…
If you have a valid password, then you
can log on to the network.
You have a valid password.
You can log on to the network.
14. Symbolic representation…
If you have a valid password, then you
can log on to the network.You have a
valid password.
You can log on to the network.
p:You have a valid password
q:You can log on to the network
15. Argument form…
If you have a valid password, then you can log on to the
network.You have a valid password.
You can log on to the network.
p:You have a valid password
q:You can log on to the network
Argument form
p → q
P
--------
q
We can write the argument as: [p ∧ (p → q) ] → q
16. Assessing validity of [p ∧ (p → q)] → q
p q p → q p ∧ (p → q) [p ∧ (p → q)] → q
F F T F T
F T T F T
T F F F T
T T T T T
The last row is where p =T and p → q =T and the argument implication is
T and so the argument is valid. It is a tautology so it is valid anyway.
•This argument form is called modus
ponens and is a valid argument.
17. Tautologies
Any argument with a tautology as the
conclusion is valid, no matter what the
premises are.
Validity is a technical term in formal logic
meaning that the conclusion cannot fail to be
true if the premises are true. Since a
tautology is always true it follows for such an
argument that the conclusion can not fail to
be true if the premises are true.
18. Another Example
If you are a Reggae lover then you know Bob Marley.
Jessica is a Reggae lover.
Therefore, Jessica knows Bob Marley.
19. Symbolic Representation
If you are a Reggae lover then you know Bob Marley.
Jessica is a Reggae lover.
Therefore, Jessica knows Bob Marley.
This argument can be condensed symbolically:
If p then q;
p;
therefore q.
20. Assessing validity of [p ∧ (p → q)] → q
p q p → q p ∧ (p → q) [p ∧ (p → q)] → q
F F T F T
F T T F T
T F F F T
T T T T T
•It is a valid argument. Do you recognise
the argument form?
*
21. Assessing validity of [p ∧ (p → q)] → q
p q p → q p ∧ (p → q) [p ∧ (p → q)] → q
F F T F T
F T T F T
T F F F T
T T T T T
• It is a valid argument. Do you recognise the
argument form?
• Remember we had called this modus ponens.
• We need to be able to recall the argument form as
we can simply quote that to determine whether
an argument is valid or not.
*
22. Another argument…
You can’t log on to the network.
If you have a valid password, you can
log on to the network.
You do not have a current password.
23. Another argument…
You can’t log on to the network.
If you have a valid password, you can
log on to the network.
You do not have a current password.
24. Argument form…
¬qYou can’t log on to the network.
If p:you have a valid password, then q you can log on
to the network.
¬p You do not have a current password.
p → q
¬ q
----------
¬ p
We can write this in shorthand as: [(p → q) ∧ ¬ q] → ¬ p
25. Assessing the argument form using a truth table
p q p → q ¬p ¬q (p → q) ∧ ¬q [(p → q) ∧ ¬q] → ¬p
F F
F T
T F
T T
26. Is it a valid argument?
p q p → q ¬p ¬q (p → q) ∧ ¬q [(p → q) ∧ ¬q] → ¬p
F F T T T T T
F T T T F F T
T F F F T F T
T T T F F F T
*
27. Is it a valid argument?
It is a valid argument.This
argument f0rm is called
modus tollens.
p q p → q ¬p ¬q (p → q) ∧ ¬q [(p → q) ∧ ¬q] → ¬p
F F T T T T T
F T T T F F T
T F F F T F T
T T T F F F T
28. StarWars
If Mr. Scott is still with us, then the power
will come on.The power comes on.
Therefore, Mr. Scott is still with us.
Valid or
Invalid?
29. Assign Logical variables
If p [Mr. Scott is still with us], then
q [the power will come on].
q [The power comes on].
Therefore, p [Mr. Scott is still with us].
30. Argument form
If p [Mr. Scott is still
with us], then q [the
power will come on]. q
[The power comes on].
Therefore, p [Mr. Scott
is still with us].
p → q
q
----------
p
This is a case of affirming the consequent
of a conditional and concluding that the
antecedent is true.
31. Assessing validity of [(p → q) ∧ q ] → p
p q p → q (p → q) ∧ q [(p → q) ∧ q]→ p
F F T F T
F T T T F
T F F F T
T T T T T
•Is this a valid argument?
*
*
32. Argument form
If p [Mr. Scott is still
with us], then q [the
power will come on]. q
[The power comes on].
Therefore, p [Mr. Scott
is still with us].
p → q
q
----------
p
This is a case of affirming the consequent of a
conditional and concluding that the antecedent is
true, The argument form is [(p → q) ∧ q] → p but
this is NOT a valid argument.
33. Rules of Inference
A rule of inference is any valid argument.
Page 21 of the Unit notes gives you all
the rules of inference.We have already
seen and proven two important ones –
modus ponens and modus tollens. Of
course ther are others as you cans ee
there!
38. What is a Proof?
A proof is a demonstration, or
argument, that shows beyond a
shadow of a doubt that a given
assertion is a logical consequence of
our axioms and definitions.
39. Kurt Godel
Kurt Godel, a brilliant mathematician and logician born and
raised in Czechoslovakia in 1906, earned his Ph.D at the
University ofVienna.
In 1931 he produced a work regarded as the single greatest
piece in mathematical logic: “On formally undecidable
proposition of Principia Mathematica and related systems I”
(originally in German). In it he showed that the German
mathematician David Hilbert’s (1862 – 1943) aim of formalizing
mathematics and demonstrating it to be complete (all facts can
be proved), consistent (nothing false can be proved) and
decidable (all propositions can be shown to be either true or
false) was unattainable.
40. Axiom
An axiom is a statement or proposition
which is regarded as being established,
accepted, or self-evidently true without
proof.
41. Direct Proof
A direct proof is a mathematical
argument that uses rules of
inference to derive the conclusion
from the premises.
43. Example
Prove the Disjunctive Syllogism by
using a Chain of Inferences.
So, we might ask, what is the
Disjunctive Syllogism?
44. Example
Prove the Disjunctive Syllogism by using a
Chain of Inferences.
So, we might ask, what is the Disjunctive
Syllogism?
It is the argument form: (p ∨ q) ∧ ¬p → q
found on p 21 of the Unit notes.
45. RTP: (p ∨ q) ∧ ¬p → q
First consider:
p ∨ q Premise 1
≡ q ∨ p Commutativity
≡ ¬(¬ q) ∨ p Double negation
≡ ¬q → p Implication
¬p Premise 2
46. RTP: (p ∨ q) ∧ ¬p → q
p ∨ q Premise 1
≡ ¬q → p Implication
¬p Premise 2
So we have, (¬q → p) ∧ ¬p
Recall: [(p → q) ∧ ¬ q] → ¬ p so applying this
inference rule, we have [(¬q → p) ∧ ¬p] → ¬ ¬q
47. RTP: (p ∨ q) ∧ ¬p → q
And putting it all together, we have:
p ∨ q Premise 1
≡ q ∨ p Commutativity
≡ ¬(¬ q) ∨ p Double negation
≡ ¬q → p Implication
¬p Premise 2
¬(¬ q) Modus tollens
Conclusion: q Double negation
Hence, (p ∨ q) ∧ ¬p → q
48. Direct Proof
• A proof with no special assumptions is called a direct proof.
• Basic Steps in Direct Proof
• Deconstruct Axioms: Take the hypothesis and turn it into a usable
form. Usually this amounts to just applying the definition. EG: k =
1(mod 3) really means 3|(k - 1) which actually means n k - 1 = 3n
• Mathematical Insights: Use your human intellect and get at “real
reason” behind theorem. For instance, looking at what we’re
trying to prove, we see that we’d really like to understand k 3. So
let’s take the cube of k! From here, we’ll have to use some algebra
to get the formula into a form usable by the final step:
• Reconstruct Conclusion: This is the reverse of step 1. At the end
of step 2 we should have a simple form that could be derived by
applying the definition of the conclusion.
49. Using symbolic derivation, prove that
q ∧ ¬(p → q) is a contradiction.
q ∧ ¬(p → q) ≡ q ∧ ¬ (¬p ∨ q) Conditional equivalence
≡ q ∧ (¬ ¬p ∧ ¬ q) …
50. Using symbolic derivation, prove that
q ∧ ¬(p → q) is a contradiction.
q ∧ ¬(p → q) ≡ q ∧ ¬ (¬p ∨ q) Conditional equivalence
≡ q ∧ (¬ ¬p ∧ ¬ q) De Morgan’s law
≡ q ∧ (¬ q ∧ ¬ ¬ p) Commutative
≡ (q ∧ ¬ q) ∧ ¬ ¬ p Associative
≡ F ∧ ¬ ¬ p) Negation
≡ F Domination
This is a direct proof.
51. Proof by Cases
Proof by exhaustion, also known as proof by cases, proof by
case analysis, complete induction or the brute force method,
is a method of mathematical proof in which the statement to
be proved is split into a finite number of cases or sets of
equivalent cases, and where each type of case is checked to see
if the proposition in question holds.
This is a method of direct proof.A proof by exhaustion typically
contains two stages:
A proof that the set of cases is exhaustive; i.e., that each
instance of the statement to be proved matches the conditions
of (at least) one of the cases.
A proof of each of the cases.
53. To prove: the sum of any two squared integers leaves
a remainder of either 0, 1 or 2 when divided by 4.
• Here, we have three cases to consider:
• Both a and b even
• One of a, b even
• Both a and b odd
• If the integers are odd, let them be 2n + 1 and 2m + 1
where n and m are integers.
• If they are even, let them be 2n and 2m where n and m
are integers.
54. Consider the case of both integers even
• If they are even, let them be 2n and 2m
where n and m are integers.
• Their squares are 4n2 and 4m2 and the sum
is 4n2 + 4m2.
• When divided by 4 this gives us a
remainder of 0.
55. Consider the case of both integers odd
• If they are odd, let them be 2n + 1 and 2m
+ 1 where n and m are integers.
• Their squares are 4n2 + 4n + 1 and 4m2 +
4m + 1 and the sum is 4n2 + 4n+ 4m2 + 2
• When divided by 4 this gives us a
remainder of 2.
56. Consider the case of one integer even and the other odd
• Let them be 2n (even) and 2m + 1 (odd)
where n and m are integers.
• Their squares are 4n2 and 4m2 + 4m + 1 and
the sum is 4n2 + 4n+ 4m2 + 1
• When divided by 4 this gives us a
remainder of 1.
57. Indirect Proof
This is basically proof using the contrapositive.
Method: For any k, assume ¬Q(k) and derive ¬P(k)
Then, by the contrapositive logical equivalence:
P(k) → Q(k) ≡ ¬ Q(k) → ¬P(k)
Offer an example of an indirect proof.
58. Show that: if n is an integer and n3 + 5 is odd, then n is even.
Let the propositions be:
• p: n3 + 5 is odd
• q: n is even
So we want to show that p → q
To prove that we shall use the contrapositive? What
do we have to show in this case?
59. The propositions are: p: n3 + 5 is odd, and q: n is even
So we want to show that p → q
The contrapositive: ¬q → ¬p.
ie If n is odd , then n3 + 5 is even.
So let n = 2k + 1 for some integer k
⇒ n3 + 5 = (2k + 1)3 + 5
= 8k3 + 3.4k2 + 3.4k + 1 + 5
= 8k3 + 12k2 + 12k + 6
= 2(4k3 + 6k2 + 6k + 3) which is even.
We have shown that n odd → n3 + 5 is even and so if
n is an integer and n3 + 5 is odd, then n is even.
Show that: if n is an integer and n3 + 5 is odd, then n is even.
60. Proof by Contradiction
• A proof method by which an assumption is made and
the argument that follows reaches a contradiction.
This means that the original assumption is wrong.
• To show that some sentence is true, we assume that it
is false (we assume the negation of that sentence) and
then show any contradiction.
• If a contradiction follows, something has gone wrong;
and if we follow our rules of logic then the only thing
that can have gone wrong was our assumption of the
negation of our conclusion. So, we must have been
wrong to assume it is false, so it must be true.
61. The set of primes is infinite.
• Assume that the set of primes is finite and let
them be p1, p2, p3 ,…, pn.
• Now form the number p1p2p3…pn + 1.This is
clearly not divisible by any of the previous
primes and hence is prime.
• We have found a prime which is not in the set
{p1, p2, p3 ,…, pn} and this is a contradiction.
• Hence, the set of primes is infinite.
62. Principle of Mathematical Induction
Find base case P(1)
Assume P(k) and prove that P(k) → P(k + 1)
Then we have ∀k P(k)
63. n ∈ Z, 6 | n3 + 5n (i.e. that 6 divides n3 + 5n )
P (1): Clearly with n = 1, 6 | 13 + 5 TRUE
Assume P(k) then 6 | k3 + 5k for some k. Now we must
show P(k) → P (k + 1)
Substituting k + 1 for k, we have (k + 1)3 + 5(k + 1)
= k3 + 3k2 + 3k + 1 + 5k + 5
= k3 + 5k + 3k2 + 3k + 6
= k3 – k + 6k + 6 + 3k(k + 1)
= k(k2 – 1) + 6k + 6 + 3k(k + 1)
= (k – 1)k(k + 1) + 6k + 6 + 3k(k + 1)
Now any three consecutive integers must contain one
which is a multiple of 2 and one which is a multiple of 3.
Thus, 6 | (k – 1)k(k + 1). Also, observe that 3k2 + 3k = 3k (k +
1) and that k(k + 1) is an even number so 6 | 3k (k + 1).
We have shown that P(k) → P(k+1) and hence we have
P(n) for all n. ■