1. Set theory is an important mathematical concept and tool that is used in many areas including programming, real-world applications, and computer science problems.
2. The document introduces some basic concepts of set theory including sets, members, operations on sets like union and intersection, and relationships between sets like subsets and complements.
3. Infinite sets are discussed as well as different types of infinite sets including countably infinite and uncountably infinite sets. Special sets like the empty set and power sets are also covered.
This document introduces some basic concepts in set theory. It defines a set as a structure representing an unordered collection of distinct objects. Set theory deals with operations on sets such as union, intersection, difference and relations between sets. It provides notations for sets and examples of basic properties of sets like equality, subsets, empty sets and infinite sets. The document also introduces concepts like cardinality, power sets, Cartesian products and Venn diagrams to represent relationships between sets.
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
Discrete Mathematics - Sets. ... He had defined a set as a collection of definite and distinguishable objects selected by the means of certain rules or description. Set theory forms the basis of several other fields of study like counting theory, relations, graph theory and finite state machines.
This document discusses sets and Venn diagrams. It defines what a set is and provides examples of sets. It describes subsets and operations that can be performed on sets such as intersection, union, complement, and difference. It explains Venn diagrams and how they are used to represent relationships between sets such as disjoint, overlapping, union, and intersection. Examples are provided to demonstrate operations on sets and drawing Venn diagrams.
Sections Included:
1. Collection
2. Types of Collection
3. Sets
4. Commonly used Sets in Maths
5. Notation
6. Different Types of Sets
7. Venn Diagram
8. Operation on sets
9. Properties of Union of Sets
10. Properties of Intersection of Sets
11. Difference in Sets
12. Complement of Sets
13. Properties of Complement Sets
14. De Morgan’s Law
15. Inclusion Exclusion Principle
The theory of sets was developed by German mathematician Georg Cantor in the late 19th century. Sets are collections of distinct objects, which can be used to represent mathematical concepts like numbers. There are different ways to represent sets, including listing elements within curly brackets or using set-builder notation to describe a property common to elements of the set. Basic set operations include union, intersection, and complement. Venn diagrams provide a visual representation of relationships between sets.
1. Set theory deals with operations between, relations among, and statements about sets.
2. A set is an unordered collection of distinct objects that can be defined by listing its elements or using set-builder notation.
3. Basic set operations include union, intersection, difference, and complement. The union of sets A and B contains all elements that are in A, B, or both. The intersection contains all elements that are in both A and B.
A relation is a set of ordered pairs that shows a relationship between elements of two sets. An ordered pair connects an element from one set to an element of another set. The domain of a relation is the set of first elements of each ordered pair, while the range is the set of second elements. Relations can be represented visually using arrow diagrams or directed graphs to show the connections between elements of different sets defined by the relation.
This document introduces some basic concepts in set theory. It defines a set as a structure representing an unordered collection of distinct objects. Set theory deals with operations on sets such as union, intersection, difference and relations between sets. It provides notations for sets and examples of basic properties of sets like equality, subsets, empty sets and infinite sets. The document also introduces concepts like cardinality, power sets, Cartesian products and Venn diagrams to represent relationships between sets.
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
Discrete Mathematics - Sets. ... He had defined a set as a collection of definite and distinguishable objects selected by the means of certain rules or description. Set theory forms the basis of several other fields of study like counting theory, relations, graph theory and finite state machines.
This document discusses sets and Venn diagrams. It defines what a set is and provides examples of sets. It describes subsets and operations that can be performed on sets such as intersection, union, complement, and difference. It explains Venn diagrams and how they are used to represent relationships between sets such as disjoint, overlapping, union, and intersection. Examples are provided to demonstrate operations on sets and drawing Venn diagrams.
Sections Included:
1. Collection
2. Types of Collection
3. Sets
4. Commonly used Sets in Maths
5. Notation
6. Different Types of Sets
7. Venn Diagram
8. Operation on sets
9. Properties of Union of Sets
10. Properties of Intersection of Sets
11. Difference in Sets
12. Complement of Sets
13. Properties of Complement Sets
14. De Morgan’s Law
15. Inclusion Exclusion Principle
The theory of sets was developed by German mathematician Georg Cantor in the late 19th century. Sets are collections of distinct objects, which can be used to represent mathematical concepts like numbers. There are different ways to represent sets, including listing elements within curly brackets or using set-builder notation to describe a property common to elements of the set. Basic set operations include union, intersection, and complement. Venn diagrams provide a visual representation of relationships between sets.
1. Set theory deals with operations between, relations among, and statements about sets.
2. A set is an unordered collection of distinct objects that can be defined by listing its elements or using set-builder notation.
3. Basic set operations include union, intersection, difference, and complement. The union of sets A and B contains all elements that are in A, B, or both. The intersection contains all elements that are in both A and B.
A relation is a set of ordered pairs that shows a relationship between elements of two sets. An ordered pair connects an element from one set to an element of another set. The domain of a relation is the set of first elements of each ordered pair, while the range is the set of second elements. Relations can be represented visually using arrow diagrams or directed graphs to show the connections between elements of different sets defined by the relation.
The document discusses sets, relations, and functions. It begins by providing examples of well-defined and not well-defined collections to introduce the concept of a set. A set is defined as a collection of well-defined objects. Standard notations for sets are introduced. Sets can be represented using a roster method by listing elements or a set-builder form using a common property. Sets are classified as finite or infinite based on the number of elements, and other set types like the empty set and singleton set are defined. Equal, equivalent, and disjoint sets are also defined.
This document provides an overview of basic set theory concepts including defining and representing sets, the number of elements in a set, comparing sets, subsets, and operations on sets including union and intersection. Key points covered are defining a set as a collection of well-defined objects, representing sets using listing, defining properties, or Venn diagrams, defining the cardinal number of a set as the number of elements it contains, comparing sets as equal or equivalent based on elements, defining subsets as sets contained within other sets, and defining union as the set of elements in either set and intersection as the set of elements common to both sets.
The document defines set concepts and their properties. It explains that a set is a collection of distinct objects, called elements. Properties discussed include how sets are denoted, elements belong or don't belong to sets, order doesn't matter, and counting each element once. It also covers set theory, Venn diagrams, ways to represent sets, types of sets (empty, finite, infinite), equal sets, subsets, cardinality, and operations like intersection, union, difference, and complement of sets. Examples are provided to illustrate each concept.
This document provides an overview of set theory, including definitions and concepts. It begins by defining a set as a collection of distinct objects, called elements or members. It describes how sets are denoted and provides examples. Key concepts covered include subsets, the empty set, set operations like union and intersection, and properties of sets. The document also discusses topics like the power set, Cartesian products, partitions, and the universal set. Overall, it serves as a comprehensive introduction to the basic ideas and terminology of set theory.
This document introduces the concept of sets in discrete mathematics. It defines what a set is and discusses how sets are represented and notated. It also covers basic set operations like union and intersection. Some key points include:
- A set is a collection of distinct objects, called elements.
- Sets can be represented either by listing elements within curly braces or using set-builder notation describing a common property.
- Basic set operations include union, intersection, subset, power set, and the empty set. Union combines elements in sets while intersection finds elements common to sets.
The document discusses integers and their properties. It defines integers as numbers that can be written without fractions or decimals, such as 21, 4, and -2048, but not 9.75 or √2. Integers include natural numbers, zero, and their negatives. They form the smallest group containing natural numbers under addition. Integers also form a ring with unique homomorphisms to other rings, characterizing their fundamental nature.
Set theory is a branch of mathematics that studies sets and their properties. A set is a collection of distinct objects, which can include numbers, points, or other sets. Some key concepts in set theory include:
- Membership and subsets, where an object is a member of a set and a set is a subset of another if all its members are also in the other set.
- Binary operations on sets like union, intersection, and complement/difference.
- The power set, which contains all possible subsets of a given set.
- Finite and infinite sets, with finite sets having a definite number of members and infinite sets not having an end. The empty set contains no members.
This document introduces basic concepts of set theory, including definitions of sets, set notation, ways to describe sets, special sets like the null set and universal set, subset and proper subset relationships, set operations like union, intersection, complement and difference. It provides examples and a Venn diagram to illustrate these concepts and concludes with some practice questions about set operations.
This document discusses functions in discrete mathematical structures. It defines a function as mapping elements from one set to unique elements in another set. A function assigns a single element from the codomain to each element in the domain. An example of a string length function maps strings to their lengths. The document also defines related terms like domain, codomain, image, and pre-image. It provides an example of a grade function and asks the reader to identify the domain, codomain, and range based on given information. Finally, it concludes with discussing functions and provides references for further reading.
This document defines and describes several key concepts in set theory:
1. A set is a collection of well-defined objects that can be clearly distinguished from one another. Examples of sets include the set of natural numbers from 1 to 50.
2. Sets can be described using either the roster method, which lists the elements within curly brackets, or the set-builder method, which defines a property for the elements.
3. Types of sets include the empty set, singleton sets containing one element, finite sets that can be counted, infinite sets that cannot be counted, equivalent sets with the same number of elements, and subsets where all elements of one set are contained within another set.
Discrete mathematics Ch1 sets Theory_Dr.Khaled.Bakro د. خالد بكروDr. Khaled Bakro
This document provides an overview of discrete mathematics and sets theory. It outlines the main topics covered in discrete mathematics including propositional logic, set theory, simple algorithms, functions, sequences, relations, counting methods, introduction to number theory, graph theory, and trees. It then defines what a discrete mathematics is and contrasts discrete vs continuous mathematics. The remainder of the document defines fundamental concepts in sets theory such as subsets, supersets, set operations, Venn diagrams, cardinality, and power sets. It also discusses ways to represent sets using arrays, linked lists, and bit strings.
This document provides an introduction to set theory. It defines what a set is and provides examples of common sets. A set can be represented in roster form by listing its elements within curly brackets or in set builder form using a characteristic property. There are different types of sets such as finite sets, infinite sets, empty sets, singleton sets, and power sets which contain all subsets. Set operations like union, intersection, difference and symmetric difference are introduced. Important concepts like subsets, equivalent sets, disjoint sets and complements are also covered.
In detail and In very simple method That can any one understand.
If you read this all you doubts about function will be clear.
because i have used very simple example and simple English words that you can pick quickly concept about functions.
#inshallah.
Discrete Mathematics - Sets. ... He had defined a set as a collection of definite and distinguishable objects selected by the means of certain rules or description. Set theory forms the basis of several other fields of study like counting theory, relations, graph theory and finite state machines.
This document introduces set theory and its importance and applications. It defines what a set is and provides examples of different types of sets such as finite, infinite, equal, subset, power and universal sets. It describes operations on sets like union, intersection and complements. The document discusses the history of set theory and its founder Georg Cantor. It provides examples of how set theory is applied in business organization and security. Venn diagrams are introduced as a way to visualize sets. An example problem is presented to demonstrate applying set theory and Venn diagrams. The document finds that set theory is widely used in many disciplines and can be applied at different levels in business operations for problems involving intersecting and non-intersecting sets.
This document discusses set operations including union, intersection, complement, and difference. It defines each operation and provides examples. Some key set identities are also covered such as commutative, associative, and distributive laws. Methods for proving set identities are discussed like using subset relationships, set builder notation, membership tables, or indicating membership with 1s and 0s. The conclusion restates that database restoration involves read and write operations on values.
This document defines and explains various concepts related to sets and relations. It discusses the four main set operations of union, intersection, complement, and difference. It then explains eight types of relations: empty, universal, identity, inverse, reflexive, symmetric, transitive, and equivalence relations. Finally, it defines partial ordering as a relation that is reflexive, antisymmetric, and transitive.
The document discusses set operations and Venn diagrams. It defines the basic set operations of intersection, union, and complement. Intersection refers to elements common to two sets, union refers to all elements in either set, and complement refers to elements not in the set. Venn diagrams use circles or regions to visually represent sets and the relationships between them. Examples demonstrate using Venn diagrams to illustrate different set operations like intersection, union, and complement. Exercises involve identifying the appropriate Venn diagram shading for expressions involving these operations.
This document defines and provides examples of different types of sets: empty sets, singleton sets, finite and infinite sets, union of sets, intersection of sets, difference of sets, subset of a set, disjoint sets, and equality of two sets. Empty sets have no elements. Singleton sets contain one element. Finite sets have a predetermined number of elements while infinite sets may be countable or uncountable. The union of sets contains all elements that are in either set. The intersection contains elements common to both sets. The difference contains elements in the first set that are not in the second. A set is a subset if all its elements are also in another set. Sets are disjoint if their intersection is empty. Two sets are equal
1. Set theory deals with operations between, relations among, and statements about sets.
2. A set is an unordered collection of distinct objects that can be defined by listing its elements or using set-builder notation.
3. Basic set operations include union, intersection, difference, and complement. The union of sets A and B contains all elements that are in A, B, or both. The intersection contains all elements that are in both A and B.
1. Set theory deals with operations between, relations among, and statements about sets.
2. A set is an unordered collection of distinct objects that can be defined by listing its elements or using set-builder notation.
3. Basic set operations include union, intersection, difference, and complement. The union of sets A and B contains all elements that are in A, B, or both. The intersection contains all elements that are in both A and B.
The document discusses sets, relations, and functions. It begins by providing examples of well-defined and not well-defined collections to introduce the concept of a set. A set is defined as a collection of well-defined objects. Standard notations for sets are introduced. Sets can be represented using a roster method by listing elements or a set-builder form using a common property. Sets are classified as finite or infinite based on the number of elements, and other set types like the empty set and singleton set are defined. Equal, equivalent, and disjoint sets are also defined.
This document provides an overview of basic set theory concepts including defining and representing sets, the number of elements in a set, comparing sets, subsets, and operations on sets including union and intersection. Key points covered are defining a set as a collection of well-defined objects, representing sets using listing, defining properties, or Venn diagrams, defining the cardinal number of a set as the number of elements it contains, comparing sets as equal or equivalent based on elements, defining subsets as sets contained within other sets, and defining union as the set of elements in either set and intersection as the set of elements common to both sets.
The document defines set concepts and their properties. It explains that a set is a collection of distinct objects, called elements. Properties discussed include how sets are denoted, elements belong or don't belong to sets, order doesn't matter, and counting each element once. It also covers set theory, Venn diagrams, ways to represent sets, types of sets (empty, finite, infinite), equal sets, subsets, cardinality, and operations like intersection, union, difference, and complement of sets. Examples are provided to illustrate each concept.
This document provides an overview of set theory, including definitions and concepts. It begins by defining a set as a collection of distinct objects, called elements or members. It describes how sets are denoted and provides examples. Key concepts covered include subsets, the empty set, set operations like union and intersection, and properties of sets. The document also discusses topics like the power set, Cartesian products, partitions, and the universal set. Overall, it serves as a comprehensive introduction to the basic ideas and terminology of set theory.
This document introduces the concept of sets in discrete mathematics. It defines what a set is and discusses how sets are represented and notated. It also covers basic set operations like union and intersection. Some key points include:
- A set is a collection of distinct objects, called elements.
- Sets can be represented either by listing elements within curly braces or using set-builder notation describing a common property.
- Basic set operations include union, intersection, subset, power set, and the empty set. Union combines elements in sets while intersection finds elements common to sets.
The document discusses integers and their properties. It defines integers as numbers that can be written without fractions or decimals, such as 21, 4, and -2048, but not 9.75 or √2. Integers include natural numbers, zero, and their negatives. They form the smallest group containing natural numbers under addition. Integers also form a ring with unique homomorphisms to other rings, characterizing their fundamental nature.
Set theory is a branch of mathematics that studies sets and their properties. A set is a collection of distinct objects, which can include numbers, points, or other sets. Some key concepts in set theory include:
- Membership and subsets, where an object is a member of a set and a set is a subset of another if all its members are also in the other set.
- Binary operations on sets like union, intersection, and complement/difference.
- The power set, which contains all possible subsets of a given set.
- Finite and infinite sets, with finite sets having a definite number of members and infinite sets not having an end. The empty set contains no members.
This document introduces basic concepts of set theory, including definitions of sets, set notation, ways to describe sets, special sets like the null set and universal set, subset and proper subset relationships, set operations like union, intersection, complement and difference. It provides examples and a Venn diagram to illustrate these concepts and concludes with some practice questions about set operations.
This document discusses functions in discrete mathematical structures. It defines a function as mapping elements from one set to unique elements in another set. A function assigns a single element from the codomain to each element in the domain. An example of a string length function maps strings to their lengths. The document also defines related terms like domain, codomain, image, and pre-image. It provides an example of a grade function and asks the reader to identify the domain, codomain, and range based on given information. Finally, it concludes with discussing functions and provides references for further reading.
This document defines and describes several key concepts in set theory:
1. A set is a collection of well-defined objects that can be clearly distinguished from one another. Examples of sets include the set of natural numbers from 1 to 50.
2. Sets can be described using either the roster method, which lists the elements within curly brackets, or the set-builder method, which defines a property for the elements.
3. Types of sets include the empty set, singleton sets containing one element, finite sets that can be counted, infinite sets that cannot be counted, equivalent sets with the same number of elements, and subsets where all elements of one set are contained within another set.
Discrete mathematics Ch1 sets Theory_Dr.Khaled.Bakro د. خالد بكروDr. Khaled Bakro
This document provides an overview of discrete mathematics and sets theory. It outlines the main topics covered in discrete mathematics including propositional logic, set theory, simple algorithms, functions, sequences, relations, counting methods, introduction to number theory, graph theory, and trees. It then defines what a discrete mathematics is and contrasts discrete vs continuous mathematics. The remainder of the document defines fundamental concepts in sets theory such as subsets, supersets, set operations, Venn diagrams, cardinality, and power sets. It also discusses ways to represent sets using arrays, linked lists, and bit strings.
This document provides an introduction to set theory. It defines what a set is and provides examples of common sets. A set can be represented in roster form by listing its elements within curly brackets or in set builder form using a characteristic property. There are different types of sets such as finite sets, infinite sets, empty sets, singleton sets, and power sets which contain all subsets. Set operations like union, intersection, difference and symmetric difference are introduced. Important concepts like subsets, equivalent sets, disjoint sets and complements are also covered.
In detail and In very simple method That can any one understand.
If you read this all you doubts about function will be clear.
because i have used very simple example and simple English words that you can pick quickly concept about functions.
#inshallah.
Discrete Mathematics - Sets. ... He had defined a set as a collection of definite and distinguishable objects selected by the means of certain rules or description. Set theory forms the basis of several other fields of study like counting theory, relations, graph theory and finite state machines.
This document introduces set theory and its importance and applications. It defines what a set is and provides examples of different types of sets such as finite, infinite, equal, subset, power and universal sets. It describes operations on sets like union, intersection and complements. The document discusses the history of set theory and its founder Georg Cantor. It provides examples of how set theory is applied in business organization and security. Venn diagrams are introduced as a way to visualize sets. An example problem is presented to demonstrate applying set theory and Venn diagrams. The document finds that set theory is widely used in many disciplines and can be applied at different levels in business operations for problems involving intersecting and non-intersecting sets.
This document discusses set operations including union, intersection, complement, and difference. It defines each operation and provides examples. Some key set identities are also covered such as commutative, associative, and distributive laws. Methods for proving set identities are discussed like using subset relationships, set builder notation, membership tables, or indicating membership with 1s and 0s. The conclusion restates that database restoration involves read and write operations on values.
This document defines and explains various concepts related to sets and relations. It discusses the four main set operations of union, intersection, complement, and difference. It then explains eight types of relations: empty, universal, identity, inverse, reflexive, symmetric, transitive, and equivalence relations. Finally, it defines partial ordering as a relation that is reflexive, antisymmetric, and transitive.
The document discusses set operations and Venn diagrams. It defines the basic set operations of intersection, union, and complement. Intersection refers to elements common to two sets, union refers to all elements in either set, and complement refers to elements not in the set. Venn diagrams use circles or regions to visually represent sets and the relationships between them. Examples demonstrate using Venn diagrams to illustrate different set operations like intersection, union, and complement. Exercises involve identifying the appropriate Venn diagram shading for expressions involving these operations.
This document defines and provides examples of different types of sets: empty sets, singleton sets, finite and infinite sets, union of sets, intersection of sets, difference of sets, subset of a set, disjoint sets, and equality of two sets. Empty sets have no elements. Singleton sets contain one element. Finite sets have a predetermined number of elements while infinite sets may be countable or uncountable. The union of sets contains all elements that are in either set. The intersection contains elements common to both sets. The difference contains elements in the first set that are not in the second. A set is a subset if all its elements are also in another set. Sets are disjoint if their intersection is empty. Two sets are equal
1. Set theory deals with operations between, relations among, and statements about sets.
2. A set is an unordered collection of distinct objects that can be defined by listing its elements or using set-builder notation.
3. Basic set operations include union, intersection, difference, and complement. The union of sets A and B contains all elements that are in A, B, or both. The intersection contains all elements that are in both A and B.
1. Set theory deals with operations between, relations among, and statements about sets.
2. A set is an unordered collection of distinct objects that can be defined by listing its elements or using set-builder notation.
3. Basic set operations include union, intersection, difference, and complement. The union of sets A and B contains all elements that are in A, B, or both. The intersection contains all elements that are in both A and B.
A set is a structure, representing an unordered collection (group, plurality) of zero or more distinct (different) objects.
Set theory deals with operations between, relations among, and statements about sets
Moazzzim Sir (25.07.23)CSE 1201, Week#3, Lecture#7.pptxKhalidSyfullah6
This document provides an overview of key concepts in set theory including:
- The definition of a set as an unordered collection of distinct elements
- Common ways to describe and represent sets such as listing elements, set-builder notation, and Venn diagrams
- Important set terminology including subset, proper subset, set equality, cardinality (size of a set), finite vs infinite sets, power set, and Cartesian product
The document uses examples and explanations to illustrate each concept over 34 pages. It appears to be lecture material introducing students to the basic foundations of set theory.
1) The document summarizes key concepts from a discrete mathematics course including sets, operations on sets, functions, sequences, and sums.
2) It covers topics like basic set theory, operations on sets like union and intersection, subsets, power sets, Cartesian products, and cardinality.
3) Examples are provided to illustrate concepts like Venn diagrams, disjoint sets, complements, and set differences.
This document discusses sets and set operations. It defines what a set is, provides examples of common sets like natural numbers and integers, and covers how to represent and visualize sets. It also defines subset and proper subset relationships between sets. Additionally, it introduces set operations like union, intersection, difference and disjoint sets. It discusses properties of these operations and how to calculate the cardinality of sets and operations.
The document provides an overview of key concepts in set theory, including:
1) The definition of a set as a collection of distinct elements, and ways to specify sets using a roster or set builder notation.
2) Types of sets such as finite, infinite, countable/uncountable sets. Operations on sets like unions, intersections, complements and differences.
3) Related concepts like subsets, universal sets, empty sets, power sets, and Cartesian products of sets.
The document summarizes key concepts in discrete mathematics including sets, operations on sets, functions, sequences, and counting techniques. It defines what a set is, ways to describe sets, and set operations like unions and intersections. Examples are given of common sets like integers, rational numbers, and real numbers. Subsets, the empty set, cardinality (size) of sets, and Venn diagrams are also explained.
This document provides an overview of sets and related concepts in discrete mathematics. Some key points covered include:
- A set is an unordered collection of distinct objects. Sets can contain numbers, words, or other sets. Order and duplicates do not matter.
- Sets are specified using curly brackets and listing elements, set-builder notation, ellipses, or capital letters. Membership is denoted using the symbol ∈.
- Basic set relationships include subsets, proper subsets, equality, the empty set, unions, and intersections. Power sets contain all possible subsets.
- Tuples are ordered lists used to specify locations in n-dimensional spaces. Cartesian products combine elements from multiple sets into ordered pairs
The document defines and explains various concepts related to sets:
- A set is a well-defined collection of objects that can be determined if an object belongs to the set or not. Sets can be defined using a roster method or set-builder notation.
- Basic set properties include sets being inherently unordered and elements being unequal. Set membership, empty sets, and common number sets are also introduced. Equality of sets, Venn diagrams, subsets, power sets, set operations, and generalized unions and intersections are further discussed.
1. The document discusses basic concepts in discrete mathematics including sets, operations on sets like union and intersection, and properties of sets like cardinality.
2. Key discrete structures like combinations, relations, and graphs are built using sets as a basic structure.
3. Set operations like union, intersection, difference, and Cartesian product are defined along with properties such as cardinality of the resulting sets.
This document introduces some basic concepts of set theory, including:
1) Defining sets by listing elements or describing properties. Common sets include real numbers, integers, etc.
2) Basic set operations like union, intersection, difference, and complement.
3) Relationships between sets like subset, proper subset, and equality.
4) Other concepts like partitions, power sets, and Cartesian products involving ordered pairs from multiple sets.
This document provides an overview of sets and set theory concepts including:
- The definition of a set and elements
- Notation used in set theory such as set membership (∈)
- Ways to describe sets such as listing elements, using properties, and recursively
- Standard sets like natural numbers (N), integers (Z), rational numbers (Q), and real numbers (R)
- Relationships between sets including subsets, supersets, unions, intersections, complements, and Cartesian products
- Basic set identities and properties like commutativity, associativity, distributivity, identities, and complements
The document introduces fundamental concepts in set theory and provides examples to illustrate set notation, descriptions,
SET
A set is a well defined collection of objects, called the “elements” or “members” of the set.
A specific set can be defined in two ways-
If there are only a few elements, they can be listed individually, by writing them between curly braces ‘{ }’ and placing commas in between. E.g.- {1, 2, 3, 4, 5}
The second way of writing set is to use a property that defines elements of the set.
e.g.- {x | x is odd and 0 < x < 100}
If x is an element o set A, it can be written as ‘x A’
If x is not an element of A, it can be written as ‘x A’
Special types of sets-
Standard notations used to define some sets:
N- set of all natural numbers
Z- set of all integers
Q- set of all rational numbers
R- set of all real numbers
C- set of all complex numbers
TYPES OF SETS
-subset
-singleton set
-universal set
-empty set
-finite set
-infinte set
-eual set
-disjoint set
-cardinal set
-power set
OPERATIONS ON SET
The four basic operations are:
1. Union of Sets
2. Intersection of sets
3. Complement of the Set
4. Cartesian Product of sets
Union of two given sets is the smallest set which contains all the elements of both the sets.
A B = {x | x A or x B}
Let a and b are sets, the intersection of two sets A and B, denoted by A B is the set consisting of elements which are in A as well as in B
A B = {X | x A and x B}
If A B= , the sets are said to be disjoint.
If U is a universal set containing set A, then U-A is called complement of a set.
The document discusses the halting problem in computer science. It introduces the halting problem as determining whether a program will halt or loop forever given an input. It then proves by contradiction that no program can solve the halting problem for all programs and inputs. It constructs an "inverter" program that does the opposite of what the hypothetical halting program says, leading to a contradiction no matter what the halting program determines for the inverter program itself. Therefore, no general halting program can exist.
This document defines fundamental concepts about sets including:
1) A set is an unordered collection of unique objects. Sets are discrete structures that form the basis for more complex structures like graphs.
2) Elements, notation for membership and non-membership, equality of sets, set-builder and extensional definitions.
3) Empty sets, singleton sets, subsets, proper subsets, cardinality of finite and infinite sets, power sets.
4) Basic set operations - union, intersection, difference, complement both absolute and relative. Venn diagrams are used to represent sets and operations visually.
The document provides information about sets and set operations in mathematics. It defines what a set is as a collection of distinct objects. It discusses basic set operations like unions, intersections, complements and subsets. It also describes special sets like the empty set, power sets, natural numbers, integers, rational numbers, real numbers and complex numbers. The document explains how to describe sets using intensional or extensional definitions and set-builder notation. It provides examples of applying basic set operations like unions, intersections and complements.
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 defines sets and key set concepts like types of sets, operations on sets, and special sets. It explains that a set is a collection of distinct objects and can be defined by listing elements or using a property. There are standard notations for sets of numbers and types like finite, infinite, empty, singleton, and power sets. The four basic set operations are defined as union, intersection, complement, and Cartesian product.
The document provides an introduction to unsupervised learning and reinforcement learning. It then discusses eigen values and eigen vectors, showing how to calculate them from a matrix. It provides examples of covariance matrices and using Gaussian elimination to solve for eigen vectors. Finally, it discusses principal component analysis and different clustering algorithms like K-means clustering.
Cross validation is a technique for evaluating machine learning models by splitting the dataset into training and validation sets and training the model multiple times on different splits, to reduce variance. K-fold cross validation splits the data into k equally sized folds, where each fold is used once for validation while the remaining k-1 folds are used for training. Leave-one-out cross validation uses a single observation from the dataset as the validation set. Stratified k-fold cross validation ensures each fold has the same class proportions as the full dataset. Grid search evaluates all combinations of hyperparameters specified as a grid, while randomized search samples hyperparameters randomly within specified ranges. Learning curves show training and validation performance as a function of training set size and can diagnose underfitting
This document provides an overview of supervised machine learning algorithms for classification, including logistic regression, k-nearest neighbors (KNN), support vector machines (SVM), and decision trees. It discusses key concepts like evaluation metrics, performance measures, and use cases. For logistic regression, it covers the mathematics behind maximum likelihood estimation and gradient descent. For KNN, it explains the algorithm and discusses distance metrics and a numerical example. For SVM, it outlines the concept of finding the optimal hyperplane that maximizes the margin between classes.
The document provides information on solving the sum of subsets problem using backtracking. It discusses two formulations - one where solutions are represented by tuples indicating which numbers are included, and another where each position indicates if the corresponding number is included or not. It shows the state space tree that represents all possible solutions for each formulation. The tree is traversed depth-first to find all solutions where the sum of the included numbers equals the target sum. Pruning techniques are used to avoid exploring non-promising paths.
The document discusses the greedy method and its applications. It begins by defining the greedy approach for optimization problems, noting that greedy algorithms make locally optimal choices at each step in hopes of finding a global optimum. Some applications of the greedy method include the knapsack problem, minimum spanning trees using Kruskal's and Prim's algorithms, job sequencing with deadlines, and finding the shortest path using Dijkstra's algorithm. The document then focuses on explaining the fractional knapsack problem and providing a step-by-step example of solving it using a greedy approach. It also provides examples and explanations of Kruskal's algorithm for finding minimum spanning trees.
The document describes various divide and conquer algorithms including binary search, merge sort, quicksort, and finding maximum and minimum elements. It begins by explaining the general divide and conquer approach of dividing a problem into smaller subproblems, solving the subproblems independently, and combining the solutions. Several examples are then provided with pseudocode and analysis of their divide and conquer implementations. Key algorithms covered in the document include binary search (log n time), merge sort (n log n time), and quicksort (n log n time on average).
What is an Algorithm
Time Complexity
Space Complexity
Asymptotic Notations
Recursive Analysis
Selection Sort
Insertion Sort
Recurrences
Substitution Method
Master Tree Method
Recursion Tree Method
This document provides an outline for a machine learning syllabus. It includes 14 modules covering topics like machine learning terminology, supervised and unsupervised learning algorithms, optimization techniques, and projects. It lists software and hardware requirements for the course. It also discusses machine learning applications, issues, and the steps to build a machine learning model.
The document discusses problem-solving agents and their approach to solving problems. Problem-solving agents (1) formulate a goal based on the current situation, (2) formulate the problem by defining relevant states and actions, and (3) search for a solution by exploring sequences of actions that lead to the goal state. Several examples of problems are provided, including the 8-puzzle, robotic assembly, the 8 queens problem, and the missionaries and cannibals problem. For each problem, the relevant states, actions, goal tests, and path costs are defined.
The simplex method is a linear programming algorithm that can solve problems with more than two decision variables. It works by generating a series of solutions, called tableaus, where each tableau corresponds to a corner point of the feasible solution space. The algorithm starts at the initial tableau, which corresponds to the origin. It then shifts to adjacent corner points, moving in the direction that optimizes the objective function. This process of generating new tableaus continues until an optimal solution is found.
The document discusses functions and the pigeonhole principle. It defines what a function is, how functions can be represented graphically and with tables and ordered pairs. It covers one-to-one, onto, and bijective functions. It also discusses function composition, inverse functions, and the identity function. The pigeonhole principle states that if n objects are put into m containers where n > m, then at least one container must hold more than one object. Examples are given to illustrate how to apply the principle to problems involving months, socks, and selecting numbers.
The document discusses relations and their representations. It defines a binary relation as a subset of A×B where A and B are nonempty sets. Relations can be represented using arrow diagrams, directed graphs, and zero-one matrices. A directed graph represents the elements of A as vertices and draws an edge from vertex a to b if aRb. The zero-one matrix representation assigns 1 to the entry in row a and column b if (a,b) is in the relation, and 0 otherwise. The document also discusses indegrees, outdegrees, composite relations, and properties of relations like reflexivity.
This document discusses logic and propositional logic. It covers the following topics:
- The history and applications of logic.
- Different types of statements and their grammar.
- Propositional logic including symbols, connectives, truth tables, and semantics.
- Quantifiers, universal and existential quantification, and properties of quantifiers.
- Normal forms such as disjunctive normal form and conjunctive normal form.
- Inference rules and the principle of mathematical induction, illustrated with examples.
The document discusses uncertainty and probabilistic reasoning. It describes sources of uncertainty like partial information, unreliable information, and conflicting information from multiple sources. It then discusses representing and reasoning with uncertainty using techniques like default logic, rules with probabilities, and probability theory. The key approaches covered are conditional probability, independence, conditional independence, and using Bayes' rule to update probabilities based on new evidence.
The document outlines the objectives, outcomes, and learning outcomes of a course on artificial intelligence. The objectives include conceptualizing ideas and techniques for intelligent systems, understanding mechanisms of intelligent thought and action, and understanding advanced representation and search techniques. Outcomes include developing an understanding of AI building blocks, choosing appropriate problem solving methods, analyzing strengths and weaknesses of AI approaches, and designing models for reasoning with uncertainty. Learning outcomes include knowledge, intellectual skills, practical skills, and transferable skills in artificial intelligence.
Planning involves representing an initial state, possible actions, and a goal state. A planning agent uses a knowledge base to select action sequences that transform the initial state into a goal state. STRIPS is a common planning representation that uses predicates to describe states and logical operators to represent actions and their effects. A STRIPS planning problem specifies the initial state, goal conditions, and set of operators. A solution is a sequence of ground operator instances that produces the goal state from the initial state.
Cricket management system ptoject report.pdfKamal Acharya
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Sachpazis_Consolidation Settlement Calculation Program-The Python Code and th...Dr.Costas Sachpazis
Consolidation Settlement Calculation Program-The Python Code
By Professor Dr. Costas Sachpazis, Civil Engineer & Geologist
This program calculates the consolidation settlement for a foundation based on soil layer properties and foundation data. It allows users to input multiple soil layers and foundation characteristics to determine the total settlement.
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2. History and Applications
• The editice of modern mathematics rests on the
concept of sets.
• Georg Cantor got his pHd in number theory.
• Important language and tool for reasoning.
• General: Reasoning and programming
• Real life: cellular phone, traffic lights, search box in
eBay, stock market, to a satellite
• Computer Science: Halting problem, Turing Machine
2
3. 3
Introduction to Set Theory
• A set is a structure, representing a
welldefined unordered collection (group,
plurality) of zero or more distinct (different)
objects called elements or member of a set.
• Set theory deals with operations on,
relations among, and statements about sets.
4. 4
Basic notations for sets
For sets, we’ll use variables S, T, U, …
• Roster or Tabular Form orListing Method: We can
denote a set S in writing by listing all of its elements in curly
braces:
– {a, b, c} is the set of whatever 3 objects are denoted by a, b,
c.
• Rule method or Set builder notation: For any
proposition P(x) over any universe of discourse, {x|P(x)} is the
set of all x such that P(x).
e.g., {x | x is an integer where x>0 and x<5 }
5. 5
Basic properties of sets
• Sets are inherently unordered:
– No matter what objects a, b, and c denote,
{a, b, c} = {a, c, b} = {b, a, c} =
{b, c, a} = {c, a, b} = {c, b, a}.
• All elements are distinct (unequal);
multiple listings make no difference!
– {a, b, c} = {a, a, b, a, b, c, c, c, c}.
– This set contains at most 3 elements!
6. 6
Definition of Set Equality
• Two sets are declared to be equal if and only if
they contain exactly the same elements.
• In particular, it does not matter how the set is
defined or denoted.
• For example: The set {1, 2, 3, 4} =
{x | x is an integer where x>0 and x<5 } =
{x | x is a positive integer whose square
is >0 and <25}
7. 7
Infinite Sets
• Conceptually, sets may be infinite (i.e., not
finite, without end, unending).
• Symbols for some special infinite sets:
N = {0, 1, 2, …} The natural numbers.
Z = {…, -2, -1, 0, 1, 2, …} The integers.
R = The “real” numbers, such as
374.1828471929498181917281943125…
• Infinite sets come in different sizes!
8. 8
Cardinality and Finiteness
• |S| (read “the cardinality of S”) is a measure of how many
different elements S has.
• E.g., ||=0, |{1,2,3}| = 3, |{a,b}| = 2,
|{{1,2,3},{4,5}}| = ____
• We say S is infinite if it is not finite.
• What are some infinite sets we’ve seen?
e.g. if S = {2, 3, 5, 7, 11, 13, 17, 19}, then |S|=8.
if S={CSC1130, CSC2110, ERG2020, MAT2510},then |S|=4.
if S = {{1,2}, {1,3}, {1,4}, {2,3}, {2,4}, {3,4}}, then |S|=6.
9. Countably infinite and
Uncountably Infinite Sets
• Finite sets are countable eg. Z.
• Uncountable sets are infinite as R.
• N, Z, R are infinite sets.
• |N| is denoted as 0.
• Any set which can be put into 1-1 correspondence
with N,Z is also countably infinite or denumerable eg.
AN, set of even Integers, set of –ve Integers, set of
prime nos.
• Thus every infinite set has countable infinite subset.
9
11. 11
Basic Set Relations: Member of
• xS (“x is in S”) is the proposition that object x is
an element or member of set S.
– e.g. 3N, ‘a’{x | x is a letter of the alphabet}
• Can define set equality in terms of relation:
S,T: S=T (x: xS xT)
“Two sets are equal iff they have all the same
members.”
• xS : (xS) “x is not in S”
12. 12
The Empty, Universal, Singleton
Set
• (“null”, “the empty set”, “void set”) is the unique set
that contains no elements whatsoever.
• = {} = {x|False}
• No matter the domain of discourse, we have the axiom
x: x.
• In any application of theory of sets, the members of all sets
under investigation usually belong to some fixed large set
called Universal Set or Universe of Discourse.
• A set having only one element is Singleton set.
13. 13
Subset and Superset Relations
• If every element in set S is element in set T, then S is called
subset of T.
• ST (“S is a subset of T”)
• We also say that S is contained in B or B contains A
• ST (“S is a superset of T”) means TS.
• ST x (xS → xT)
• S, SS.
• Note S=T ST ST.
• means (ST), i.e. x(xS xT)
• Eg. S={1,2,3}, B=(1,2,3,4,5}
TS /
A B
14. 14
Sets and Subsets
set equality C D C D D C= ( ) ( )
subsets A B x x A x B [ ]
][
)]()([
][
BxAxx
BxAxx
BxAxxBA
Fact: If , then |A| <= |B|.
15. 15
Properties of Subsets
• If A={4, 8, 12, 16} and B={2, 4, 6, 8, 10, 12, 14, 16},
then but
• because every element in A is an element of A.
• for any A because the empty set has no elements.
• If A is the set of prime numbers and
B is the set of odd numbers, then
16. 16
Proper (Strict) Subsets & Supersets
• ST (“S is a proper subset of T”) means that ST but
. Similar for ST.
ST /
S
T
Venn
Diagram
equivalent
of ST
Example:
{1,2} {1,2,3}
Fact: If A = B, then |A| = |B|.
Fact: If , then |A| < |B|.
17. 17
Sets and Subsets (common
notations)
(a) Z=the set of integers={0,1,-1,2,-1,3,-3,...}
(b) N=the set of nonnegative integers or natural numbers
(c) Z+=the set of positive integers
(d) Q=the set of rational numbers={a/b| a,b is integer, b not zero}
(e) Q+=the set of positive rational numbers
(f) Q*=the set of nonzero rational numbers
(g) R=the set of real numbers
(h) R+=the set of positive real numbers
(i) R*=the set of nonzero real numbers
(j) C=the set of complex numbers
18. 18
Examples of sets
The set of all polynomials with degree at most three:
{1, x, x2, x3, 2x+3x2,…}.
The set of all n-bit strings:
{000…0, 000…1, …, 111…1}
The set of all triangles without an obtuse angle:
{ , ,… }
The set of all graphs with four nodes:
{ , , , ,…}
19. 19
The Power Set Operation
• The power set P(S) of a set S is the set of all
subsets of S. P(S) = {x | xS}.
• E.g. P({a,b}) = {, {a}, {b}, {a,b}}.
• Sometimes P(S) is written 2S.
Note that for finite S, |P(S)| = 2|S|.
• It turns out that |P(N)| > |N|.
There are different sizes of infinite sets!
20. 20
Sets Are Objects, Too!
• The objects that are elements of a set may
themselves be sets.
• E.g. let S={x | x {1,2,3}}
then P(S)={,
{1}, {2}, {3},
{1,2}, {1,3}, {2,3},
{1,2,3}}
• Note that 1 {1} {{1}} !!!!
21. 21
Ordered n-tuples
• For nN, an ordered n-tuple or a sequence
of length n is written (a1, a2, …, an). The
first element is a1, etc.
• These are like sets, except that duplicates
matter, and the order makes a difference.
• Note (1, 2) (2, 1) (2, 1, 1).
• Empty sequence, singlets, pairs, triples,
quadruples, quintuples, …, n-tuples.
22. 22
The Union Operator
• For sets A, B, their union AB is the set
containing all elements that are either in A,
or (“”) in B (or, of course, in both).
• Formally, A,B: AB {x | xA xB}.
• Note that AB contains all the elements of
A and it contains all the elements of B:
A, B: (AB A) (AB B)
24. 24
The Intersection Operator
• For sets A, B, their intersection AB is the
set containing all elements that are
simultaneously in A and (“”) in B.
• Formally, A,B: AB{x | xA xB}.
• Note that AB is a subset of A and it is a
subset of B:
A, B: (AB A) (AB B)
26. 26
Disjointedness
• Two sets A, B are called
disjoint (i.e., unjoined)
iff their intersection is
empty. (AB=)
• Example: the set of even
integers is disjoint with
the set of odd integers.
Help, I’ve
been
disjointed!
27. 27
Set Difference
• For sets A, B, the difference of A and B,
written A−B, is the set of all elements that
are in A but not B.
• A − B : x xA xB
= x ( xA → xB )
• Also called:
The complement of B with respect to A.
28. 28
Set Difference Examples
• {1,2,3,4,5,6} − {2,3,5,7,9,11} =
___________
• Z − N = {… , -1, 0, 1, 2, … } − {0, 1, … }
= {x | x is an integer but not a nat. #}
= {x | x is a negative integer}
= {… , -3, -2, -1}
{1,4,6}
29. 29
Set Difference - Venn Diagram
• A-B is what’s left after B
“takes a bite out of A”
Set A Set B
Set
A−B
Chomp!
30. 30
Set Complements
• The universe of discourse can itself be
considered a set, call it U.
• The complement of A, written , is the
complement of A w.r.t. U, i.e., it is U−A.
• E.g., If U=N,
A
,...}7,6,4,2,1,0{}5,3{ =
31. 31
More on Set Complements
• An equivalent definition, when U is clear:
}|{ AxxA =
A
U
A
32. 32
Ring Sum (Symmetric
Difference)
• Let A and B be two non empty sets then
ring sum of A and B is set of all elements
which are either in A or in B but not in
both.
• Thus A⊕B={x | x ∈ A∪B but ∉ A∩B}
= {x|(x∈A and x∉B)or (x∈B and x ∉A)}
33. 33
Cartesian Products of Sets
• For sets A, B, their Cartesian product
AB : {(a, b) | aA bB }.
• E.g. {a,b}{1,2} = {(a,1),(a,2),(b,1),(b,2)}
• Note that for finite A, B, |AB|=|A||B|.
• Note that the Cartesian product is not
commutative: AB: AB =BA.
• Extends to A1 A2 … An...
34. 34
Cartesian Product
• Let A be the set of letters, i.e. {a,b,c,…,x,y,z}.
• Let B be the set of digits, i.e. {0,1,…,9}.
AxA is just the set of strings with two letters.
BxB is just the set of strings with two digits.
AxB is the set of strings where the first character is a letter
and the second character is a digit.
Definition: Given two sets A and B, the Cartesian product A
x B is the set of all ordered pairs (a,b), where a is in A and b
is in B. (1,2) ≠ (2,1)
35. 35
Laws of set theory
• Identity: A=A AU=A
• Domination: AU=U A=
• Idempotent: AA = A = AA
• Involution:
• Commutative: AB=BA AB=BA
• Associative: A(BC)=(AB)C
A(BC)=(AB)C
AA =)(
36. 36
Laws of set theory
• Distributive: A∩(BC)=(A∩B)(A∩C)
A (BC)=(AB)(AC)
• Properties of complement:
AAc =U AAc =
c =U Uc=
37. 37
DeMorgan’s Law for Sets
• Exactly analogous to (and derivable from) DeMorgan’s
Law for propositions.
BABA
BABA
=
=
38. 38
Set Operations and the Laws of
Set Theory
s dual of s (sd)
U
U
Theorem (The Principle of Duality)
39. 39
Partition of sets
A collection of nonempty sets {A1, A2, …, An} is a partition
of a set A if and only if
A1, A2, …, An are mutually disjoint (or pairwise disjoint).
e.g. Let A be the set of integers.
A1 = {x A | x = 3k+1 for some integer k}
A2 = {x A | x = 3k+2 for some integer k}
A3 = {x A | x = 3k for some integer k}
Then {A1,A2,A3} is a partition of A
40. Partition of sets
e.g. Let A be the set of integers divisible by 6.
A1 be the set of integers divisible by 2.
A2 be the set of integers divisible by 3.
Then {A1,A2} is not a partition of A, because A1 and A2 are not disjoint,
and also A A1 A2 (so both conditions are not satisfied).
e.g. Let A be the set of integers.
Let A1 be the set of negative integers.
Let A2 be the set of positive integers.
Then {A1,A2} is not a partition of A, because A ≠A1 A2
as 0 is contained in A but not contained in A1 A2
41. 41
(Addition Principle / Sum Rule)
If sets A and B are disjoint, then
|A B| = |A| + |B|
A B
What if A and B are not disjoint?
47. 47
Counting and Venn Diagrams
• In a class of 50 college freshmen, 30 are studying BASIC,
25 studying PASCAL, and 10 are studying both. How
many freshmen are studying either computer language?
| | | | | | | |A B A B A B = + −
A B
10 1520