Showing posts with label #Set. Show all posts
Showing posts with label #Set. Show all posts

Table of content

Table of Content 

Formulas: Differentiation 

Integration: Type 1 

Integration: Type 2

Calculus of Several Variables 

            1
           2
           3
Continuity of function of two variables
           4
           5
           6
           7
           8
           9
Maxima and minima
.          10
Lagrange multipliers method 

       Assignment - 1

       11. Double Integration 

       12. Double Integration: Polar form

       13. Double Integration: By Change of Variable

       14. Double Integration: By Change of Order

       15. Application of Double Integration 

       16. Application of Double Integration: Area 

       17. Application of Double Integration: Volume

       18. Application of Double Integration: Mass, Center of Mass

       19. Application of Double Integration: Moment of Inertia 

        21. Triple Integration 

       22. Triple Integration: Polar form

       33. Triple Integration: By Change of Variable

       24.Triple Integration: By Change of Order

       25. Application of Triple Integration 

       26. Application of Triple Integration: Volume

       27. Application of Triple Integration: Mass, Center of Mass

       38. Application of Double Integration: Moment of Inertia 

       39. Application of Double Integration:  

Computational and Statistical Optimization 

L1: Big Data Matrix

L2: Approximate Matrix Multiplication  

L3: Random Sampling 

L4: Randomized Algorithms 

L8: LDLT Factorization 

Cholesky Decomposition 

L10: Block Elimination Method 

Linear Algebra 

Chapter 1: Matrix

Chapter 2: Row Echelon Form

Chapter 3: Reduced Row Echelon Form

Chapter 4: Rank of a Matrix

Chapter 5: Solution of System of Equations

Chapter 6: Eigenvalues and Eigenvectors

Other chapters will be updated soon.

Mathematics for Biotechnology and Data Science 

Chapter 1: Set Theory 

Chapter 2: Operation of Sets 

Chapter 3: Application of Set Theory 

Chapter 4: Venn Diagram  

Chapter 5: Relation  

Chapter 6: MAPPING OR FUNCTIONS 

Chapter 8: Inverse of a Function 

Test 1: Set Theory  

Test 2: Set, Relation and Function 

Calculus 

Chapter 1: Limit of Function 

Chapter 4: Successive Differentiation 

Ordinary Differential Equation

Chapter 1: First Order Differential Equations using Separation of Variables

Chapter 2: Application of ODE

Chapter 3: Solution of Homogeneous Differential Equations 

 

Probability and Statistics

Chapter 1: #Probability 

Chapter 2: #Conditional Probability  

Chapter 3: #Baye's theorem 

Some Questions of Probability 


Chapter 5: Relation

Return to Table of Content 

Mathematics for Biotechnology and Data Science 

Chapter 1: Set Theory 

Chapter 2: Operation of Sets 

Chapter 3: Application of Set Theory 

Chapter 4: Venn Diagram  

Chapter 5: Relation  

Chapter 6: MAPPING OR FUNCTIONS 

Chapter 8: Inverse of a Function 

Relations

1.     Introduction 

:     Relations: 

As we know and already studied about notions of relations and functions, domain, co-domain, and range, along with different types of specific real-valued functions and their graphs. The concept of the term ‘relation’ in mathematics has been drawn from the meaning of relation in the English language, according to which two objects or quantities are related if there is a recognisable connection or link between the two objects or quantities. Let A be the set of students of Class XII of a school, and B be the set of students of Class XI of the same school. Then some of the examples of relations from A to B are

(1) 

(2) 

(3) 

(4) 

(5) 

However, abstracting from this, we define mathematically a relation R from A to B as an arbitrary subset of .

If (a, b) R, we say that a is related to b under the relation  and we write as a  b. In general, (a, b) R, we do not bother whether there is a recognisable connection or link between a and b. As we already know the functions are special kind of relations.

In this chapter, we will study different types of relations and functions, composition of functions, invertible functions and binary operations.

2.     Types of Relations

In this section, we would like to study different types of relations. We know that a relation in a set A is a subset of . Thus, the empty set  and  are two extreme relations. For illustration, consider a relation R in the set A = {1, 2, 3, 4} given by . This is the empty set, as no pair (a, b) satisfies the condition a – b = 10. Similarly,  is the whole set , as all pairs (a, b) in  satisfy . These two extreme examples lead us to the following definitions.

 

A.    Empty Relation

A relation R in a set A is called empty relation, if no element of A is related to any element of A, i.e., .

B.    Universal Relation

A relation R in a set A is called universal relation, if each element of A is related to every element of A, i.e., R = A × A.

Both the empty relation and the universal relation are sometimes called trivial relations.

Example 1 Let A be the set of all students of a boy’s school. Show that the relation R in A given by  is the empty relation and R' = {(a, b) : the difference between heights of a and b is less than 3 meters} is the universal relation.

Solution Since the school is boy’s school, no student of the school can be sister of any student of the school. Hence, , showing that R is the empty relation. It is also obvious that the difference between heights of any two students of the school has to be less than 3 meters. This shows that  is the universal relation.

Example 2: Set A is the set of all students of a boy’s school. Show that the relation R on P given by

.

Solution It is obvious that the difference between the heights of any two students of the school has to be less than 5 metres. Therefore, it can be concluded that  for all .

R is the universal-relation on set P.

Example 3 Let set . Let a relation R be defined on A as . Show that R is and empty relation.

Solution The Cartesian product is the set of all possible ordered pairs of elements from set A.

 

The relation R is defined by the condition . You must check each ordered pair in  to see if it satisfies this condition.

For , for , and for

Then , for  and for

Then , for  and for

none of the ordered pairs from  satisfy the condition , the  contain no elements.

The relation  is an empty relation.

Remark In earlier class, we have seen two ways of representing a relation, namely raster method and set builder method. However, a relation R in the set {1, 2, 3, 4} defined by  is also expressed as  if and only if  by many authors. We may also use this notation, as and when convenient. If , we say that a is related to b and we denote it as .

One of the most important relation, which plays a significant role in Mathematics, is an equivalence relation. To study equivalence relation, we first consider three types of relations, namely reflexive, symmetric and transitive.

C.    Equivalence Relation

A relation R in a set A is called equivalence relation then the following 3 condition must be satisfied:

a.     Reflexive, if , for every

b.    Symmetric, if  implies that , for all .

c.     Transitive, if  and  implies that , for all .

Remark A relation R in a set A is said to be an equivalence relation if R is reflexive, symmetric and transitive.

Example 4 Let  be the set of all triangles in a plane with R a relation in T given by . Show that R is an equivalence relation.

Solution R is reflexive, since every triangle is congruent to itself. Further,  is congruent to  is congruent to . Hence, R is symmetric. Moreover,  is congruent to T2 and T2 is congruent to  is congruent to . Therefore, R is an equivalence relation.

Example 5 Let L be the set of all lines in a plane and R be the relation in L defined as . Show that R is symmetric but neither reflexive nor transitive.

Text Box: Fig 1.1Solution R is not reflexive, as a line  cannot be perpendicular to itself, i.e., . R is symmetric as  

 

 

.

 

R is not transitive. Indeed, if is perpendicular to  and  is perpendicular to  , then  can never be perpendicular to . In fact,  is parallel to , i.e., .

Example 6 Show that the relation R in the set {1, 2, 3} given by  is reflexive but neither symmetric nor transitive.

Solution R is reflexive, since (1, 1), (2, 2) and (3, 3) lie in R. Also, R is not symmetric, as  but . Similarly, R is not transitive, as  and  but .

Example 7 Show that the relation R in the set Z of integers given by  is an equivalence relation.

Solution R is reflexive, as  for all a Z. Further, , then . Therefore, . Hence, , which shows that R is symmetric. Similarly, if  and , then  and  are divisible by 2. Now,  is even. So, . This shows that R is transitive. Thus, R is an equivalence relation in Z.

Example 8 Let R be the relation defined in the set  by . Show that R is an equivalence relation. Further, show that all the elements of the subset {1, 3, 5, 7} are related to each other and all the elements of the subset {2, 4, 6} are related to each other, but no element of the subset {1, 3, 5, 7} is related to any element of the subset {2, 4, 6}.

Solution Given any element a in A, both a and a must be either odd or even, so that . Further,   both a and b must be either odd or even . Similarly,  and   all elements a, b, c, must be either even or odd simultaneously . Hence, R is an equivalence relation. Further, all the elements of {1, 3, 5, 7} are related to each other, as all the elements of this subset are odd. Similarly, all the elements of the subset {2, 4, 6} are related to each other, as all of them are even. Also, no element of the subset {1, 3, 5, 7} can be related to any element of {2, 4, 6}, as elements of {1, 3, 5, 7} are odd, while elements of {2, 4, 6} are even.


Assignment: Probability and Statistics Basic

Sticky Ad Probability Problems with Detailed Solutions Click each question to expand the detailed interpretation and solution. ...