In this chapter, the Logic, contrapositive, converse, inference, discrete mathematics, discrete structure, argument, conjunction, disjunction, negation are well explained.
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 introduces some basic concepts in propositional logic. It defines propositional logic as the study of how simple propositions combine to form more complex propositions. It discusses statements as descriptions that can be true or false, and provides examples. It also introduces logical connectives like negation, conjunction, disjunction, implication and biconditional, and shows how they combine atomic propositions into compound propositions. Truth tables are provided to illustrate the truth values of compound propositions formed with different connectives.
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 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.
This document summarizes Chapter 1 of the textbook "Discrete Mathematics" by R. Johnsonbaugh. It covers the topics of logic, proofs, and propositional logic. Key points include:
- Logic is the study of correct reasoning and is used in mathematics and computer science.
- A proposition is a statement that can be determined as true or false. Connectives like AND, OR, and NOT can combine propositions.
- Truth tables define the truth values of compound propositions formed from connectives.
- Quantifiers like "for all" and "there exists" are used to make universal and existential statements.
- A proof is a logical argument establishing the truth of a theorem using definitions, ax
Discrete Math Chapter 1 :The Foundations: Logic and ProofsAmr Rashed
The document describes Chapter 1 of a textbook on discrete mathematics and its applications. Chapter 1 covers propositional logic, propositional equivalences, predicates and quantifiers, and nested quantifiers. It defines basic concepts such as propositional variables, logical operators, truth tables, logical equivalence, predicates, quantifiers, and translating between logical expressions and English sentences. Examples are provided to illustrate different logical equivalences and how to negate quantified statements. The chapter introduces key foundations of logic and proofs that are important for discrete mathematics.
The document discusses proofs by contraposition. It explains that a statement of the form "if p then q" can be proven by showing its contrapositive "if not q then not p" is true. It provides examples of proofs using this method, including proving if n^2 is even then n is even, if m + n is even then m and n have the same parity, and if 3n + 2 is odd then n is odd. Homework exercises are provided applying this proof technique.
The document provides definitions and explanations of key concepts in propositional logic, including:
- Propositions, truth tables, and logical connectives like negation, conjunction, disjunction, implication, biconditional, and exclusive or.
- Well-formed formulas and logical properties like tautology, contradiction, substitution instance, and valid consequence.
- Logical equivalences between expressions using different connectives, such as showing an implication is equivalent to its contrapositive using truth tables.
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 introduces some basic concepts in propositional logic. It defines propositional logic as the study of how simple propositions combine to form more complex propositions. It discusses statements as descriptions that can be true or false, and provides examples. It also introduces logical connectives like negation, conjunction, disjunction, implication and biconditional, and shows how they combine atomic propositions into compound propositions. Truth tables are provided to illustrate the truth values of compound propositions formed with different connectives.
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 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.
This document summarizes Chapter 1 of the textbook "Discrete Mathematics" by R. Johnsonbaugh. It covers the topics of logic, proofs, and propositional logic. Key points include:
- Logic is the study of correct reasoning and is used in mathematics and computer science.
- A proposition is a statement that can be determined as true or false. Connectives like AND, OR, and NOT can combine propositions.
- Truth tables define the truth values of compound propositions formed from connectives.
- Quantifiers like "for all" and "there exists" are used to make universal and existential statements.
- A proof is a logical argument establishing the truth of a theorem using definitions, ax
Discrete Math Chapter 1 :The Foundations: Logic and ProofsAmr Rashed
The document describes Chapter 1 of a textbook on discrete mathematics and its applications. Chapter 1 covers propositional logic, propositional equivalences, predicates and quantifiers, and nested quantifiers. It defines basic concepts such as propositional variables, logical operators, truth tables, logical equivalence, predicates, quantifiers, and translating between logical expressions and English sentences. Examples are provided to illustrate different logical equivalences and how to negate quantified statements. The chapter introduces key foundations of logic and proofs that are important for discrete mathematics.
The document discusses proofs by contraposition. It explains that a statement of the form "if p then q" can be proven by showing its contrapositive "if not q then not p" is true. It provides examples of proofs using this method, including proving if n^2 is even then n is even, if m + n is even then m and n have the same parity, and if 3n + 2 is odd then n is odd. Homework exercises are provided applying this proof technique.
The document provides definitions and explanations of key concepts in propositional logic, including:
- Propositions, truth tables, and logical connectives like negation, conjunction, disjunction, implication, biconditional, and exclusive or.
- Well-formed formulas and logical properties like tautology, contradiction, substitution instance, and valid consequence.
- Logical equivalences between expressions using different connectives, such as showing an implication is equivalent to its contrapositive using truth tables.
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.
This document provides an overview of the topics covered in a discrete structures course, including logic, sets, relations, functions, sequences, recurrence relations, combinatorics, probability, and graphs. It defines discrete mathematics as the study of mathematical structures that have distinct, separated values rather than varying continuously. Some examples given are problems involving a fixed number of islands/bridges or connecting a set number of cities with telephone lines. Logic is introduced as the study of valid vs. invalid arguments, and basic logical concepts like statements, truth values, compound statements, logical connectives, negation, and truth tables are outlined.
This document contains lecture notes on the principle of mathematical induction. It includes examples, exercises, and solutions working through proofs using induction for equations numbered 23-2 through 23-25. Each section is labeled with the relevant equation and includes steps to prove or solve problems related to that equation inductively.
This document discusses probability theory and its applications. It begins by defining probability as a measure of how likely an event is to occur between 0 and 1. It then provides examples of calculating theoretical probability for simple events like a coin toss or dice roll. The document goes on to explain how probability theory is applied in many areas such as mathematics, statistics, science, and engineering. It provides examples of using probability for risk assessment in fields like finance, biology, and engineering reliability. Finally, it discusses how probability assessments influence decisions and have changed society.
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.
Content:
1- Mathematical proof (what and why)
2- Logic, basic operators
3- Using simple operators to construct any operator
4- Logical equivalence, DeMorgan’s law
5- Conditional statement (if, if and only if)
6- Arguments
Propositional Logic
CMSC 56 | Discrete Mathematical Structure for Computer Science
August 17, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
- The document discusses the mathematical foundations of computer science, including topics like mathematical logic, set theory, algebraic structures, and graph theory.
- It specifically focuses on mathematical logic, defining statements, atomic and compound statements, and various logical connectives like negation, conjunction, disjunction, implication, biconditional, and their truth tables.
- It also discusses logical concepts like tautologies, contradictions, contingencies, logical equivalence, and tautological implication through the use of truth tables and logical formulas.
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.
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.
This document discusses recurrence relations and their use in defining sequences. It introduces key concepts like recurrence relations, initial conditions, explicit formulas, and solving recurrence relations using techniques like backtracking or finding the characteristic equation. As examples, it examines the Fibonacci sequence and linear homogeneous recurrence relations of varying degrees.
Combinatorics is a subfield of discrete mathematics that focuses on counting combinations and arrangements of discrete objects. It involves counting the number of ways to put things together into various combinations. Some key rules in combinatorics include the sum rule, which states that the number of ways to accomplish either of two independent tasks is the sum of the number of ways to accomplish each task individually. The product rule states that the number of ways to accomplish two independent tasks is the product of the number of ways to accomplish each task. Generating functions can be used to efficiently represent counting sequences by coding terms as coefficients of a variable in a formal power series. They allow problems involving counting and arrangements to be solved using operations with formal power series.
This document discusses proof by contradiction in mathematics. It begins by defining proof by contradiction as proving the truth of a statement by showing that assuming the statement is false leads to a contradiction. The document then provides examples of proofs by contradiction, including:
1) Proving there is no greatest integer by supposing there is a greatest integer N and showing that N+1 would also be an integer, contradicting that N was the greatest.
2) Proving the square root of 2 is irrational by supposing it is rational and showing this leads to a contradiction.
3) Explaining the general steps in a proof by contradiction: assume the statement is false, show this assumption leads to a contradiction, and thus
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.
This document provides an overview of propositional logic and logical operators. It defines basic concepts like propositions, logical connectives, and truth tables. Compound propositions are formed by combining one or more propositions using logical operators like conjunction, disjunction, negation, implication, equivalence, exclusive or, and others. Computer representations of logic using bits are also discussed, where true and false map to 1 and 0, and bitwise logic operators correspond directly to the logical connectives. Precedence rules for logical operators are defined.
This document provides an overview of mathematical logic. It defines key concepts such as propositions, truth values, logical connectives like negation, conjunction, disjunction, implication, biconditional, and quantifiers. Propositions are statements that can be either true or false. Logical connectives combine propositions and quantifiers specify whether statements apply to all or some cases. Truth tables are used to determine the truth values of statements combined with logical connectives. The document also discusses predicates, universal and existential quantification, and DeMorgan's laws relating negation and quantification.
The binomial theorem provides a formula for expanding binomial expressions of the form (a + b)^n. It states that the terms of the expansion are determined by binomial coefficients. Pascal's triangle is a mathematical arrangement that shows the binomial coefficients and can be used to determine the coefficients in a binomial expansion. The proof of the binomial theorem uses mathematical induction to show that the formula holds true for any positive integer value of n.
Propositional Equivalences
CMSC 56 | Discrete Mathematical Structure for Computer Science
August 23, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
The document discusses truth tables, which are used to determine if compound statements are true or false. It provides examples of truth tables for negation, conjunction, and disjunction. A conjunction is true only when both statements are true, while a disjunction is true when at least one statement is true. Truth tables can have more than two statements, with each additional statement doubling the number of possible cases.
1) Logic is the study of reasoning and is the foundation of computer science and mathematics.
2) A proposition is a statement that is either true or false, such as "Islamabad is the capital of Pakistan." Logical operators combine propositions using connectives like AND, OR, and NOT.
3) Truth tables define the truth values of compound propositions based on the truth values of the component propositions.
This document provides an outline for a course on discrete mathematics. It covers the following topics in 3 sentences or less each:
Logic and proof, including propositions, rules of inference, and proofs. Sets and set operations, functions, sequences, induction and recursion, counting, permutation, relations, graphs and paths, and trees. It lists the textbook "Discrete Mathematics and Its Applications" by Kenneth H. Rosen as required reading. Today's outline focuses on logic, propositions, truth tables, and conditional statements. It provides examples of propositions, truth tables, logical operators like conjunction, disjunction, implication, and biconditional. It also discusses the contrapositive, converse, and inverse of conditional statements.
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.
This document provides an overview of the topics covered in a discrete structures course, including logic, sets, relations, functions, sequences, recurrence relations, combinatorics, probability, and graphs. It defines discrete mathematics as the study of mathematical structures that have distinct, separated values rather than varying continuously. Some examples given are problems involving a fixed number of islands/bridges or connecting a set number of cities with telephone lines. Logic is introduced as the study of valid vs. invalid arguments, and basic logical concepts like statements, truth values, compound statements, logical connectives, negation, and truth tables are outlined.
This document contains lecture notes on the principle of mathematical induction. It includes examples, exercises, and solutions working through proofs using induction for equations numbered 23-2 through 23-25. Each section is labeled with the relevant equation and includes steps to prove or solve problems related to that equation inductively.
This document discusses probability theory and its applications. It begins by defining probability as a measure of how likely an event is to occur between 0 and 1. It then provides examples of calculating theoretical probability for simple events like a coin toss or dice roll. The document goes on to explain how probability theory is applied in many areas such as mathematics, statistics, science, and engineering. It provides examples of using probability for risk assessment in fields like finance, biology, and engineering reliability. Finally, it discusses how probability assessments influence decisions and have changed society.
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.
Content:
1- Mathematical proof (what and why)
2- Logic, basic operators
3- Using simple operators to construct any operator
4- Logical equivalence, DeMorgan’s law
5- Conditional statement (if, if and only if)
6- Arguments
Propositional Logic
CMSC 56 | Discrete Mathematical Structure for Computer Science
August 17, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
- The document discusses the mathematical foundations of computer science, including topics like mathematical logic, set theory, algebraic structures, and graph theory.
- It specifically focuses on mathematical logic, defining statements, atomic and compound statements, and various logical connectives like negation, conjunction, disjunction, implication, biconditional, and their truth tables.
- It also discusses logical concepts like tautologies, contradictions, contingencies, logical equivalence, and tautological implication through the use of truth tables and logical formulas.
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.
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.
This document discusses recurrence relations and their use in defining sequences. It introduces key concepts like recurrence relations, initial conditions, explicit formulas, and solving recurrence relations using techniques like backtracking or finding the characteristic equation. As examples, it examines the Fibonacci sequence and linear homogeneous recurrence relations of varying degrees.
Combinatorics is a subfield of discrete mathematics that focuses on counting combinations and arrangements of discrete objects. It involves counting the number of ways to put things together into various combinations. Some key rules in combinatorics include the sum rule, which states that the number of ways to accomplish either of two independent tasks is the sum of the number of ways to accomplish each task individually. The product rule states that the number of ways to accomplish two independent tasks is the product of the number of ways to accomplish each task. Generating functions can be used to efficiently represent counting sequences by coding terms as coefficients of a variable in a formal power series. They allow problems involving counting and arrangements to be solved using operations with formal power series.
This document discusses proof by contradiction in mathematics. It begins by defining proof by contradiction as proving the truth of a statement by showing that assuming the statement is false leads to a contradiction. The document then provides examples of proofs by contradiction, including:
1) Proving there is no greatest integer by supposing there is a greatest integer N and showing that N+1 would also be an integer, contradicting that N was the greatest.
2) Proving the square root of 2 is irrational by supposing it is rational and showing this leads to a contradiction.
3) Explaining the general steps in a proof by contradiction: assume the statement is false, show this assumption leads to a contradiction, and thus
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.
This document provides an overview of propositional logic and logical operators. It defines basic concepts like propositions, logical connectives, and truth tables. Compound propositions are formed by combining one or more propositions using logical operators like conjunction, disjunction, negation, implication, equivalence, exclusive or, and others. Computer representations of logic using bits are also discussed, where true and false map to 1 and 0, and bitwise logic operators correspond directly to the logical connectives. Precedence rules for logical operators are defined.
This document provides an overview of mathematical logic. It defines key concepts such as propositions, truth values, logical connectives like negation, conjunction, disjunction, implication, biconditional, and quantifiers. Propositions are statements that can be either true or false. Logical connectives combine propositions and quantifiers specify whether statements apply to all or some cases. Truth tables are used to determine the truth values of statements combined with logical connectives. The document also discusses predicates, universal and existential quantification, and DeMorgan's laws relating negation and quantification.
The binomial theorem provides a formula for expanding binomial expressions of the form (a + b)^n. It states that the terms of the expansion are determined by binomial coefficients. Pascal's triangle is a mathematical arrangement that shows the binomial coefficients and can be used to determine the coefficients in a binomial expansion. The proof of the binomial theorem uses mathematical induction to show that the formula holds true for any positive integer value of n.
Propositional Equivalences
CMSC 56 | Discrete Mathematical Structure for Computer Science
August 23, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
The document discusses truth tables, which are used to determine if compound statements are true or false. It provides examples of truth tables for negation, conjunction, and disjunction. A conjunction is true only when both statements are true, while a disjunction is true when at least one statement is true. Truth tables can have more than two statements, with each additional statement doubling the number of possible cases.
1) Logic is the study of reasoning and is the foundation of computer science and mathematics.
2) A proposition is a statement that is either true or false, such as "Islamabad is the capital of Pakistan." Logical operators combine propositions using connectives like AND, OR, and NOT.
3) Truth tables define the truth values of compound propositions based on the truth values of the component propositions.
This document provides an outline for a course on discrete mathematics. It covers the following topics in 3 sentences or less each:
Logic and proof, including propositions, rules of inference, and proofs. Sets and set operations, functions, sequences, induction and recursion, counting, permutation, relations, graphs and paths, and trees. It lists the textbook "Discrete Mathematics and Its Applications" by Kenneth H. Rosen as required reading. Today's outline focuses on logic, propositions, truth tables, and conditional statements. It provides examples of propositions, truth tables, logical operators like conjunction, disjunction, implication, and biconditional. It also discusses the contrapositive, converse, and inverse of conditional statements.
The document contains 10 logic puzzles or riddles posed as questions. It then provides definitions of logic, including that logic is the study of reasoning and analyzing patterns of reasoning. It discusses several key concepts in logic, including propositions, truth values, logical operators like conjunction and disjunction, and how they are represented using truth tables. Finally, it discusses some logical forms like conditional statements and biconditionals, and how natural language can differ from logical interpretation.
discrete structures and their introductionZenLooper
This document provides an introduction to a discrete structures/mathematics course. It discusses how discrete structures are relevant to computer science given computers use binary digits. It also lists some applications of discrete structures in areas like management science and networks. The document outlines topics to be covered in the course like logic, sets, functions, and graphs. It provides information on assessments, textbooks, and contact information for the instructor.
Discrete mathematics is the study of mathematical structures that are discrete rather than continuous. It considers objects that vary in a discrete way, such as digital watches showing integers of time, rather than analog watches with continuous hands. Problems in discrete mathematics cover non-continuous domains and consider questions about connecting cities with telephone lines or visiting islands with bridges without crossing any bridge twice. Logic and propositions are also key aspects of discrete mathematics, including defining statements, propositional variables, compound propositions using operators, truth tables, and negation, conjunction, disjunction and other operations.
- 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 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.
This document discusses mathematical foundations of computer science. It covers topics such as statements (propositions), logic operators (NOT, AND, OR), compound statements, logical equivalence, conditional statements, and arguments. Specifically, it defines statements as sentences that are either true or false. It introduces logic operators and how they can be used to construct new statements from old ones. It also discusses logical forms such as truth tables and De Morgan's laws. Finally, it discusses conditional statements, logical equivalence, and valid arguments.
This document provides an introduction to mathematical analysis by outlining key topics including:
- An overview of analysis and its focus on real-valued functions of a single real variable and their analytic properties like limits, continuity, and differentiability.
- A review of logic including definitions of statements, connectives, implications, and equivalences.
- An introduction to proof, discussing the difference between conjectures, theorems, lemmas, and corollaries and how proofs demonstrate statements are universally true or find counter examples.
This document provides information about the CSE 115/ENGR 160 Discrete Mathematics course taught by Professor Ming-Hsuan Yang at UC Merced. It lists the lecture and lab times, as well as the instructor and TAs' contact information. Grading policies and topics to be covered are also outlined, including logic, proof, sets, graphs and Boolean algebra. The required textbook is listed.
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 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 introduces key concepts in propositional logic including propositions, propositional variables, truth tables, logical connectives, predicates, quantification, and translation of statements between propositional logic and English. Some key points:
- Propositions are declarative sentences that are either true or false. Propositional variables represent propositions. Logical connectives like negation, conjunction, and disjunction are used to form compound propositions.
- Truth tables define the truth values of compound propositions based on the truth values of their component propositions.
- Predicates involve variables and become propositions when values are assigned to the variables.
- Quantifiers like universal and existential quantification express the extent to which a
This document discusses propositional logic and covers topics like propositions, common logical operators like negation and conjunction, proving the equivalence of logical formulas, constructing logical formulas based on truth tables, and simplifying logical formulas using laws like De Morgan's laws and distribution laws. Examples are provided for each topic to illustrate key concepts in propositional logic.
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 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 provides examples of its data structures and applications. It explains that propositional logic can represent statements using variables and logical connectives like implication, conjunction, disjunction and negation. An example problem is given about a student's cleverness and passing that is translated into propositional logic statements. Backtracking is also discussed as a way to determine if a propositional logic sentence is satisfiable by searching for a solution. Some improvements to backtracking mentioned are the pure symbol heuristic and unit clause heuristic.
Discrete structures are the study of discrete, mathematical objects and structures that are composed of distinct, separable parts. The course provides a theoretical foundation of discrete structures as they apply to computer science. It aims to help students develop mathematical maturity and problem solving skills needed for advanced courses. Key topics covered include propositional logic, truth tables, and logical connectives like negation, conjunction, disjunction, implication, equivalence and their roles in representing relationships between propositions.
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We will explore Vertex AI - Model Garden powered experiences, we are going to learn more about the integration of these generative AI APIs. We are going to see in action what the Gemini family of generative models are for developers to build and deploy AI-driven applications. Vertex AI includes a suite of foundation models, these are referred to as the PaLM and Gemini family of generative ai models, and they come in different versions. We are going to cover how to use via API to: - execute prompts in text and chat - cover multimodal use cases with image prompts. - finetune and distill to improve knowledge domains - run function calls with foundation models to optimize them for specific tasks. At the end of the session, developers will understand how to innovate with generative AI and develop apps using the generative ai industry trends.
PyData London 2024: Mistakes were made (Dr. Rebecca Bilbro)Rebecca Bilbro
To honor ten years of PyData London, join Dr. Rebecca Bilbro as she takes us back in time to reflect on a little over ten years working as a data scientist. One of the many renegade PhDs who joined the fledgling field of data science of the 2010's, Rebecca will share lessons learned the hard way, often from watching data science projects go sideways and learning to fix broken things. Through the lens of these canon events, she'll identify some of the anti-patterns and red flags she's learned to steer around.
1. Discrete
Structures
or
Mathematics
Muhammad Nawaz, (PhD, UK)
Assistant Professor (Multimedia Systems)
PhD and MS-Computer Science Programs Coordinator
Centre for Excellence in Information Technology
IMSciences Peshawar- Pakistan
2. Introduction
• Discrete mathematics is the part of mathematics devoted to the study
of discrete objects.
• Here “Discrete” means consisting of unconnected elements.
• Examples
• How many ways are there to choose a valid password on a computer
system?
• What is the probability of winning a lottery?
• Is there a link between two computers in a network?
• How can I identify spam email messages?
3. • How can I encrypt a messages so that no unintended recipient can
read it?
• What is the shortest path between two cities using a transportation
system?
• How can a list of integers be sorted so that the integers are in
increasing order?
• How many steps are required to do such a sorting?
• How can it be proved that a sorting algorithm correctly sorts a list?
• How can a circuit that adds two integers be designed?
• How many valid Internet addresses are there?
4. • More generally, discrete mathematics is used whenever objects are
counted, when relationships between finite (or countable) sets are
studied, and when processes involving a finite number of steps are
analyzed.
5. Why Study Discrete Mathematics?
• There are several important reasons for studying discrete
mathematics.
• First, through this course you can develop your mathematical
maturity: that is, your ability to understand and create mathematical
arguments.
• Second, discrete mathematics is the gate way to more advanced
courses in all parts of the mathematical sciences i.e. data structures,
algorithms, database theory, automata theory, formal languages,
compiler theory, computer security, and operating systems.
6. • Also, discrete mathematics contains the necessary mathematical
background for solving problems in operations research ( including
many discrete optimization techniques), chemistry, engineering,
biology, and soon.
7. Logic?????
• Logic is the study of the principles and methods that distinguish
between a valid and invalid argument.
8. Propositions
• A proposition is a declarative sentence (that is, a sentence that
declares a fact) that is either true or false, but not both.
• Examples
1. Islamabad is the capital of Pakistan.
2. Madras is the capital of India.
3. 1+1=2.
4. 2+2=3.
• Note that sentences 1 and 3 are true but 2 an 4 are false but in any
case all the four sentences are proposition according to the definition
9. • Some sentences that are not propositions are given as follows.
1. What time is it?
2. Read this carefully.
3. x+1=2.
4. x+y=z.
• Sentences 1 and 2 are not propositions because they are not declarative
sentences. Sentences 3 and 4 are not propositions because they are
neither true nor false.
• Note that each of sentences 3 and 4 can be turned into a proposition if we
assign values to the variables.
10. Proposition Variables
• Propositions are denoted by letters i.e. p, q, r, s.
• The truth value of proposition is denoted by T and False values are
denoted by F.
11. Atomic Propositions
• Atomic proposition is the proposition that cannot be divided into
more simpler propositions.
• For example
• “Dr. Sajid Anwar is the assistant professor in IMS.
• 50>40
• Ali is rich
12. Molecular Proposition
• When atomic propositions are combined with the help of connective,
molecular propositions are formed. (and, or, not).
• For example consider the following propositions
• p: Pakistan is situated in South Asia
• q: Islamabad is the capital of Pakistan
• By using connective “and” a molecular proposition can be formed as;
• r: Pakistan is situated in South Asia and Islamabad is the capital of
Pakistan.
13. Truth Table
• A truth table displays the relationship between the truth values of
propositions.
• It is constructed from simpler propositions.
• Let see how to construct a truth tables for different forms of
propositions???
14. Negation
• Let p be a proposition. The negation of p, denoted by ~p (also
denoted by p), is the statement
“It is not the case that p.”
• The proposition ~p is read “not p.” The truth value of the negation of
p, ~p, is the opposite of the truth value of p.
• For example
• “Today is Friday”
• The negation of the given sentence would be
• “Today is not Friday”
15. • “Ali’s smart phone has at least 32GB of memory”
• The negation of this sentence would be
• “Ali’s smart phone does not have at least 32GB of memory”
• Or simply
• “Ali’s smart phone has less than 32GB of memory”
16. Truth table for Negation
• Truth table for negation is given
in the table shown.
• T represents true value and F
represents false value.
17. Conjunction ()
• If p and q are statements, then
the conjunction of p and q is “p
and q”, denoted as “p q”.
• It is true when, and only when,
both p and q are true. If either p
or q is false, or if both are false,
p q is false.
• Truth table for conjunction can
be shown as;
18. Disjunction ()
• If p & q are statements, then the
disjunction of p and q is “p or
q”, denoted as “p q”.
• It is true when at least one of p
or q is true and is false only
when both p and q are false.
• Truth table for disjunction is
shown as;
19. Conditional statements or Implications
• Let p and q be propositions. The
conditional statement p → q is the
proposition “if p, then q.” The
conditional statement p → q is
false when p is true and q is false,
and true otherwise.
• In the conditional statement p → q,
p is called the hypothesis (or
antecedent or premise) and q is
called the conclusion (or
consequence).
• Truth table for implication is shown
as;
p q p q
T T T
T F F
F T T
F F T
20. Implication Examples
• If there is flood then the crops will destroy.
• Hassan will pass the exam if he studies hard.
• If it rains then the streets get wet.
• If It snows then we will go on skiing.
• “If 1 = 1, then 3 = 3.” TRUE
• “If 1 = 1, then 2 = 3.” FALSE
• “If 1 = 0, then 3 = 3.” TRUE
• “If 1 = 2, then 2 = 3.” TRUE
• “If 1 = 1, then 1 = 2 and 2 = 3.” FALSE
• “If 1 = 3 or 1 = 2 then 3 = 3.” TRUE
21. Inverse of a Conditional Statement
• The inverse of the conditional statement p q is ~p ~q
• A conditional and its inverse are not equivalent as could be seen from
the truth table.
22. Examples
1. If today is Friday, then 2 + 3 = 5.
If today is not Friday, then 2 + 3 5.
2. If it snows today, I will ski tomorrow.
If it does not snow today I will not ski tomorrow.
3. If P is a square, then P is a rectangle.
If P is not a square then P is not a rectangle.
4. If my car is in the repair shop, then I cannot get to class.
If my car is not in the repair shop, then I shall get to the class.
23. Converse of a conditional statement
• The converse of the conditional
statement p q is q p
• A conditional and its converse
are not equivalent i.e., is not
a commutative operator.
24. Examples
1. If today is Friday, then 2 + 3 = 5.
If 2 + 3 = 5, then today is Friday.
2. If it snows today, I will ski tomorrow.
I will ski tomorrow only if it snows today.
3. If P is a square, then P is a rectangle.
If P is a rectangle then P is a square.
4. If my car is in the repair shop, then I cannot get to class.
If I cannot get to the class, then my car is in the repair shop.
25. Contrapositive of a conditional statement
• The contrapositive of the conditional statement p q is ~ q ~ p
• A conditional and its contrapositive are equivalent.
1. If today is Friday, then 2 + 3 = 5.
If 2 + 3 5, then today is not Friday.
2. If it snows today, I will ski tomorrow.
I will not ski tomorrow only if it does not snow today.
3. If P is a square, then P is a rectangle.
If P is not a rectangle then P is not a square.
4. If my car is in the repair shop, then I cannot get to class.
If I get to the class, then my car is not in the repair shop.
26. Biconditional
• If p and q are statement
variables, the biconditional of p
and q is
• “p if and only if, q” and is
denoted p q. if and only if
abbreviated iff.
• The double headed arrow " "
is the biconditional operator.
• Truth table for biconditional
statement is shown as;
27. Examples
• True or false?
1. “1+1 = 3 if and only if earth is flat”
TRUE
2. “Sky is blue iff 1 = 0”
FALSE
3. “Milk is white iff birds lay eggs”
TRUE
4. “33 is divisible by 4 if and only if horse has four legs”
FALSE
28. Compound Propositions
• A string consisting of variables, parenthesis and connectives is called a
compound proposition.
• Example
• ~(p q), ~(p Ʌ q), (p(p q r))
Note: “2n” is used to create a truth table for the given expression.
Where n is the number of variable used in the expression.
29. Tautology
• A tautology is a statement form
that is always true regardless of
the truth values of the
statement variables.
• A tautology is represented by
the symbol “T”.
• EXAMPLE: The statement form p
~ p is tautology
30. Contradiction
• A contradiction is a statement
form that is always false
regardless of the truth values of
the statement variables.
• A contradiction is represented
by the symbol “c”.
• EXAMPLE:
• The statement form p ~ p is a
contradiction.
p ~ p p ~ p
T F F
F T F
31. Exclusive Or
• When or is used in its exclusive sense, the statement “p or q” means
“p or q but not both” or “p or q and not p and q” which translates
into symbols as:
• (p q) ~ (p q)
• Which is abbreviated as:
• p q
• or p XOR q
32. • Basically
• p q ≡ (p Ʌ ~q) v (~p Ʌ q)
• ≡ [p Ʌ ~q) v ~p] Ʌ [(p Ʌ ~q) v q]
• ≡ (p v q) Ʌ ~(p Ʌ q)
• ≡ (p v q) Ʌ (~p v ~q)
•
p q pq pq ~ (pq) (pq) ~ (pq)
T T T T F F
T F T F T T
F T T F T T
F F F F T F
TRUTH TABLE FOR EXCLUSIVE OR:
33. Logical Equivalence
• Two compound propositions A, B are regarded as logically equivalent,
if they have the same truth values.
OR
• Two compound propositions A, B are logically equivalent if and only if
A B is a tautology.
• Examples
34. • p Ʌ T p Laws of identity
• p v F p
• p Ʌ p p Idempotent Law
• p v p p
• ~(~p) p Double Negative
• p v q q v p
• p Ʌ q q Ʌ p
• Commutative Law
• ((p v q) Ʌ r) ((p v (q v r))
• ((p v (q Ʌ r) ((p v q) Ʌ (p v r))
• Distributive Laws
• ((p v q) v r) ((p v (q v r))
• ((p Ʌ q) Ʌ r) ((p Ʌ (q Ʌ r))
• Associative Laws
• ~(p v q) ~p Ʌ ~q
• ~(p Ʌ q) ~p v ~q
• Demargan’s Laws
• p q ~q ~p Contrapositive
35. Applying Laws Of Logic
• Using law of logic, simplify the statement form
• p [~(~p q)]
• Solution:
• p [~(~p q)] p [~(~p) (~q)] DeMorgan’s Law
• p [p(~q)] Double Negative Law
• [p p](~q) Associative Law for
• p (~q) Indempotent Law
36. • Using Laws of Logic, verify the logical equivalence
• ~ (~ p q) (p q) p
• Solution:
• ~(~p q) (pq) (~(~p) ~q) (p q) DeMorgan’s Law
• (p ~q) (p q) Double Negative Law
p (~q q) Distributive Law
• p c Negation Law
• p Identity Law
37. Translating From English To Symbols
• Let p = “It is hot”, and q = “It is sunny”
• SENTENCE SYMBOLIC FORM
• It is not hot. ~ p
• It is hot and sunny. p q
• It is hot or sunny. p q
• It is not hot but sunny. ~ p q
• It is neither hot nor sunny. ~ p ~ q
38. • p = “Islamabad is the capital of Pakistan”
• q = “17 is divisible by 3”
• p Ʌ q = “Islamabad is the capital of Pakistan and 17 is divisible by 3”
• p v q = “Islamabad is the capital of Pakistan or 17 is divisible by 3”
• ~p = “It is not the case that Islamabad is the capital of Pakistan” or
simply
• “Islamabad is not the capital of Pakistan”
39. • Let h = “Zia is healthy”
• w = “Zia is wealthy”
• s = “Zia is wise”
• Translate the compound statements to symbolic form:
1. Zia is healthy and wealthy but not wise. (h w) (~s)
2. Zia is not wealthy but he is healthy and wise. ~w (h s)
3. Zia is neither healthy, wealthy nor wise. ~h ~w ~s
40. Translating From Symbols To English
• Let m = “Ali is good in Mathematics”
• c = “Ali is a Computer Science student”
• Translate the following statement forms into plain English:
• ~ c Ali is not a Computer Science student
• c m Ali is a Computer Science student or good in Maths.
• m ~c Ali is good in Maths but not a Computer Science
student
• A convenient method for analyzing a compound statement is to make
a truth table for it.
41. Rules of Inference
• In propositional logic there are certain statements that are accepted
as axioms- statements that do not need to be proved. An axiom is
therefore a statement whose truth is self evident.
• On the other hand a theorem is a statement that is shown to be true.
It can be demonstrated that a theorem is true with the sequence of
statements that form an argument, called a proof.
• To construct proofs, methods are needed to derive new statements
from the old ones. Here axioms are used.
• The rules of inference tie together the step of a proof.
42. Rules of Inference
• Let P an Q are two compound
propositions. P logically implies
Q (i.e. P => Q) if and only if P
Q is tautology.
• Example
• p (p v q) Addition
• p Ʌ q p Simplification
• (p c) ~p Absurdity
• (p Ʌ (p q)) q Modus ponens
• ((p q) Ʌ ~q => ~p
• Modus tollens
• ((p q) Ʌ (q r)) => p r
• Transitivity of Implication
• ((p q) Ʌ (q r)) (p r)
• Hypothetical syllogism
• ((p v q) Ʌ ~p) q
• Disjunctive syllogism
43. Argument
• An argument is a list of statements called premises (or assumptions or
hypotheses) followed by a statement called the conclusion.
• P1 Premise
• P2 Premise
• P3 Premise
• . . . . .. . . . .
• Pn Premise
• ______________
• C Conclusion
• NOTE The symbol read “therefore,” is normally placed just before the
conclusion.
44. Valid argument
• An argument is valid if the
conclusion is true when all the
premises are true.
• Alternatively, an argument is
valid if conjunction of its
premises imply conclusion. That
is (P1 P2 P3 . . . Pn) C
is a tautology.
EXAMPLE:
Show that the following argument form is valid:
pq
p
q
SOLUTION
premises conclusion
FFTFF
TFTTF
FTFFT
TTTTT
qppqqp
critical row
45. Invalid argument
• An argument is invalid if the
conclusion is false when all the
premises are true.
• Alternatively, an argument is
invalid if conjunction of its
premises does not imply
conclusion.
• EXAMPLE Show that the
following argument form is invalid:
• p q
• q
• p
SOLUTION premises conclusion
FFTFF
FTTTF
TFFFT
TTTTT
pqpqqp
critical row
46. Example
• Use truth table to determine the
argument form
• p q
• p ~q
• p r
• r
• is valid or invalid.
premises conclusion
FTTFFFF
TTTFTFF
FTTTFTF
TTTTTTF
FFTTFFT
TTTTTFT
FFFTFTT
TTFTTTT
rprp~qpqrqp
Critical rows
47. Word Form Example
• If Tariq is not on team A, then Hameed is
on team B.
• If Hameed is not on team B, then Tariq is
on team A. Tariq is not on team A or
Hameed is not on team B.
• SOLUTION
• Let
• p = Tariq is on team A
• q = Hameed is on team B
• Then the argument is
• ~ p q
• ~ q p
• ~ p ~ q
p q ~p q ~p q ~p ~q
T T T T F
T F T T T
F T T T T
F F F F T
48. • Argument is invalid. Because there are three critical rows ( Remember
that the critical rows are those rows where the premises have truth
value T) and in the first critical row conclusion has truth value F. (Also
remember that we say an argument is valid if in all critical rows
conclusion has truth value T).
49. • If at least one of these two
numbers is divisible by 6, then
the product of these two
numbers is divisible by 6.
• Neither of these two numbers is
divisible by 6.
• The product of these two
numbers is not divisible by 6.
• SOLUTION
• Let p = at least one of these
two numbers is divisible by 6.
• q = product of these two
numbers is divisible by 6.
• Then the argument become in
these symbols
• p q
• ~ p
• ~ q
50. p q p q ~p ~q
T T T F F
T F F F T
F T T T F
F F T T T
• Here there are two critical rows
the 3rd and 4th rows. The
conclusion of the third row is F.
This shows that the given
argument is invalid.
51. • If I got an Eid bonus, I’ll buy a
stereo.
• If I sell my motorcycle, I’ll buy a
stereo.
• If I get an Eid bonus or I sell my
motorcycle, then I’ll buy a stereo.
• SOLUTION:
• Let
• e = I got an Eid bonus
• s = I’ll buy a stereo
• m = I sell my motorcycle
• The argument is
• e s
• m s
• e m s
52. e s me sm s emem s
T T T T T T T
T T F T T T T
T F T F F T F
T F F F T T F
F T T T T T T
F T F T T F T
F F T T F T F
F F F T T F T
• The argument is valid. Because
there are five critical rows (
Remember that the critical rows
are those rows where the
premises have truth value T) and
in all critical row conclusion has
truth value T. (Also remember
that we say an argument is valid
if in all critical rows conclusion
has truth value T).
53. • An interesting teacher keeps me
awake. I stay awake in Discrete
Mathematics class. Therefore, my
Discrete Mathematics teacher is
interesting.
• Solution:
• t: my teacher is interesting
a: I stay awake
• m: I am in Discrete Mathematics
class the argument to be tested is
• t a,
• a m
• m t
t a m t a a m m t
T T T T T T
T T F T F F
T F T F F T
T F F F F F
F T T T T F
F T F T F F
F F T T F F
F F F T F F