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Answered on 13 Apr Learn Unit I: Relations and Functions

Nazia Khanum

A relation R:A→AR:A→A is said to be reflexive if, for every element aa in the set AA (where AA is a non-empty set), the ordered pair (a,a)(a,a) belongs to the relation RR. In simpler terms, reflexive relations include every element paired with itself in the set. read more

A relation R:A→AR:A→A is said to be reflexive if, for every element aa in the set AA (where AA is a non-empty set), the ordered pair (a,a)(a,a) belongs to the relation RR. In simpler terms, reflexive relations include every element paired with itself in the set.

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Answered on 13 Apr Learn Unit I: Relations and Functions

Nazia Khanum

A relation R:A→AR:A→A is said to be symmetric if for every pair of elements a,ba,b in set AA, whenever (a,b)(a,b) is in RR, then (b,a)(b,a) must also be in RR. In other words, if aa is related to bb, then bb must be related to aa as well, for all a,ba,b in AA. read more

A relation R:A→AR:A→A is said to be symmetric if for every pair of elements a,ba,b in set AA, whenever (a,b)(a,b) is in RR, then (b,a)(b,a) must also be in RR. In other words, if aa is related to bb, then bb must be related to aa as well, for all a,ba,b in AA.

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Answered on 13 Apr Learn Unit I: Relations and Functions

Nazia Khanum

A universal relation in the context of relational databases refers to a relation (or table) that contains all possible combinations of tuples from the sets involved. In simpler terms, it includes every possible pair of elements from its constituent sets. For example, let's consider a universal relation... read more

A universal relation in the context of relational databases refers to a relation (or table) that contains all possible combinations of tuples from the sets involved. In simpler terms, it includes every possible pair of elements from its constituent sets.

For example, let's consider a universal relation that represents the Cartesian product of the sets A = {1, 2} and B = {x, y}. The universal relation would contain all possible combinations of elements from A and B:

yaml
Universal Relation: (1, x) (1, y) (2, x) (2, y)

In this example, the universal relation contains all possible combinations of elements from set A and set B.

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Answered on 13 Apr Learn Unit I: Relations and Functions

Nazia Khanum

To prove that the function f:R→Rf:R→R given by f(x)=2xf(x)=2x is one-to-one (injective), we need to show that if f(x1)=f(x2)f(x1)=f(x2), then x1=x2x1=x2 for all x1,x2x1,x2 in the domain. Let's assume f(x1)=f(x2)f(x1)=f(x2): 2x1=2x22x1=2x2 Now, we'll solve for x1x1 and x2x2: x1=x2x1=x2 Since... read more

To prove that the function f:R→Rf:R→R given by f(x)=2xf(x)=2x is one-to-one (injective), we need to show that if f(x1)=f(x2)f(x1)=f(x2), then x1=x2x1=x2 for all x1,x2x1,x2 in the domain.

Let's assume f(x1)=f(x2)f(x1)=f(x2): 2x1=2x22x1=2x2

Now, we'll solve for x1x1 and x2x2: x1=x2x1=x2

Since x1=x2x1=x2, it means that for any two inputs x1x1 and x2x2 that produce the same output under the function f(x)=2xf(x)=2x, those inputs must be the same. This proves that the function f(x)=2xf(x)=2x is one-to-one.

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Answered on 13 Apr Learn Unit I: Relations and Functions

Nazia Khanum

To prove that (f+g)∘h=f∘h+g∘h(f+g)∘h=f∘h+g∘h, let's start by understanding what (f+g)∘h(f+g)∘h means: (f+g)∘h(x)=(f+g)(h(x))=f(h(x))+g(h(x))(f+g)∘h(x)=(f+g)(h(x))=f(h(x))+g(h(x)) Now, let's find (f∘h+g∘h)(x)(f∘h+g∘h)(x): f∘h(x)+g∘h(x)=f(h(x))+g(h(x))f∘h(x)+g∘h(x)=f(h(x))+g(h(x)) This expression is... read more

To prove that (f+g)∘h=f∘h+g∘h(f+g)∘h=f∘h+g∘h, let's start by understanding what (f+g)∘h(f+g)∘h means:

(f+g)∘h(x)=(f+g)(h(x))=f(h(x))+g(h(x))(f+g)∘h(x)=(f+g)(h(x))=f(h(x))+g(h(x))

Now, let's find (f∘h+g∘h)(x)(f∘h+g∘h)(x):

f∘h(x)+g∘h(x)=f(h(x))+g(h(x))f∘h(x)+g∘h(x)=f(h(x))+g(h(x))

This expression is identical to what we found for (f+g)∘h(x)(f+g)∘h(x). Hence, we can conclude that (f+g)∘h=f∘h+g∘h(f+g)∘h=f∘h+g∘h.

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Answered on 13 Apr Learn Unit I: Relations and Functions

Nazia Khanum

To find (g∘f)(x)(g∘f)(x), which is the composition of g(x)g(x) with f(x)f(x), we substitute f(x)f(x) into g(x)g(x) wherever we see xx. Given: f(x)=∣x∣f(x)=∣x∣ g(x)=∣5x+1∣g(x)=∣5x+1∣ We first find f(x)f(x): f(x)=∣x∣f(x)=∣x∣ And then substitute it into g(x)g(x): g(f(x))=∣5(∣x∣)+1∣g(f(x))=∣5(∣x∣)+1∣ Now,... read more

To find (g∘f)(x)(gf)(x), which is the composition of g(x)g(x) with f(x)f(x), we substitute f(x)f(x) into g(x)g(x) wherever we see xx.

Given:

f(x)=∣x∣f(x)=∣x∣ g(x)=∣5x+1∣g(x)=∣5x+1∣

We first find f(x)f(x):

f(x)=∣x∣f(x)=∣x∣

And then substitute it into g(x)g(x):

g(f(x))=∣5(∣x∣)+1∣g(f(x))=∣5(∣x∣)+1∣

Now, ∣x∣∣x∣ can be either xx if x≥0x≥0 or −x−x if x<0x<0.

So, ∣5(∣x∣)+1∣∣5(∣x∣)+1∣ will be:

If x≥0x≥0: g(f(x))=∣5x+1∣g(f(x))=∣5x+1∣

If x<0x<0: g(f(x))=∣−5x+1∣g(f(x))=∣−5x+1∣

 
 
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Answered on 06 Apr Learn Unit III: Calculus

Sadika

We know, tan−1a+cot−1a=π2 Therefore, cot(tan−1a+cot−1a)=cotπ2=0 read more

We know,

tan1a+cot1a=π2
 
Therefore,
cot(tan1a+cot1a)=cotπ2=0

 

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Answered on 06 Apr Learn Unit III: Calculus

Sadika

To determine the principal value of read more

To determine the principal value of

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Answered on 06 Apr Learn Matrices

Sadika

The identity matrix of order n is denoted by I∩ It is a square matrix with dimensions n×nn×n where all the elements on the main diagonal (from the top left to the bottom right) are 1, and all other elements are 0. read more

The identity matrix of order n is denoted by I∩

It is a square matrix with dimensions n×nn×n where all the elements on the main diagonal (from the top left to the bottom right) are 1, and all other elements are 0.

 
 
 
 
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Answered on 06 Apr Learn Matrices

Sadika

A square matrix is a matrix that has the same number of rows and columns. In other words, it is a matrix where the number of rows is equal to the number of columns. For example, a 3×33×3 matrix and a 4×44×4 matrix are both square matrices because they have 3 rows and 3 columns,... read more

A square matrix is a matrix that has the same number of rows and columns. In other words, it is a matrix where the number of rows is equal to the number of columns.

For example, a 3×33×3 matrix and a 4×44×4 matrix are both square matrices because they have 3 rows and 3 columns, and 4 rows and 4 columns, respectively.

Square matrices are commonly encountered in various mathematical contexts, such as linear algebra, where they are used to represent linear transformations, systems of linear equations, and many other mathematical structures.

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