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If A is a non–singular matrix and the eigen values of A are 2 , 3 , -3 then the eigen values of A-1 are
  • a)
    2 , 3 , - 3
  • b)
    1/2, 1/3, -1/3
  • c)
    2|A|, 3|A|, -3|A|
  • d)
    None of these
Correct answer is option 'B'. Can you explain this answer?

Tanishq Chavan answered
If λ1 ,λ2 ,λ3 ....λare the eigen values of a non–singular matrix A, then A-1 has the eigen values  1/λ1 ,1/λ2 ,1/λ3 ....1/λn Thus eigen values of A-1are 1/2, 1/3, -1/3

The number of linearly independent eigenvectors of 
  • a)
    0    
  • b)
    1    
  • c)
    2    
  • d)
    Infinit e 
Correct answer is 'B'. Can you explain this answer?

Pranjal Sen answered
Number of linear independent vectors is equal to the sum of Geometric Multiplicity of eigen values. Here only eigen value is 2. To find Geometric multiplicity find n-r of (matrix-2I), where n is order and r is rank. Rank of obtained matrix is 1 and n=2 so n-r=1. Therefore the no of linearly independent eigen vectors is 1

The eigenvalues of
  • a)
    -19,5,37
  • b)
    19,-5,-37
  • c)
    2,-3,7
  • d)
    3,-5,37
Correct answer is option 'A'. Can you explain this answer?

Avinash Sharma answered
The eigenvalues of an upper triangular matrix are simply the diagonal entries of the matrix.
Hence 5, -19, and 37 are the eigenvalues of the matrix. Alternately, look atd
λ = 5, -19, 37

If -1 , 2 , 3 are the eigen values of a square matrix A then the eigen values of A2 are
  • a)
    -1 , 2 , 3
  • b)
    1, 4, 9
  • c)
    1, 2, 3
  • d)
    None of these
Correct answer is option 'B'. Can you explain this answer?

Aditya Patel answered
If λ1 ,λ2 ,λ3 ....λare the eigen values of  a matrix A, then A2 has the eigen values  λ12 ,λ22 ,λ32 ....λn2 So, eigen values of Aare 1, 4, 9.

Eigen values of a matrix    are 5 and 1. What are the eigen values of the matrix S2  = SS?
  • a)
    1 and 25  
  • b)
    6 and 4  
  • c)
    5 and 1  
  • d)
    2 and 10 
Correct answer is option 'A'. Can you explain this answer?

EduRev GATE answered
We know If λ be the eigen value of A ⇒λ2 is an eigen value of A2 .
For S matrix, if eigen values are λ1, λ2, λ3,... then for S² matrix, the eigen values will be λ²1 λ²2 λ²3......
For S matrix, if eigen values are 1 and 5 then for S² matrix, the eigen values are 1 and 25

If 2 and 4 are the eigen values of A then the eigenvalues of AT are
  • a)
    1/2, 1/4 
  • b)
    2, 4
  • c)
    4, 16
  • d)
    None of these
Correct answer is option 'B'. Can you explain this answer?

Sanvi Kapoor answered
The eigenvalues of a matrix A are the roots of the characteristic equation of A, which are invariant under the transpose operation. This means that the matrix A and its transpose AT have the same eigenvalues.
Given that 2 and 4 are the eigenvalues of A, the eigenvalues of AT will also be 2 and 4.

In an M × N matrix such that all non-zero entries are covered in a rows and b column. Then the maximum number of non-zero entries, such that no two are on the same row or column, is 
  • a)
    ≤ a + b    
  • b)
    ≤ max (a, b)  
  • c)
    ≤ min[ M –a, N–b]    
  • d)
    ≤ min  {a, b} 
Correct answer is option 'D'. Can you explain this answer?

Suppose a < b, for example let a = 3, b= 5, then we can put non-zero entries only in 3 rows and 5 columns. So suppose we put non-zero entries in any 3 rows in 3 different columns. Now we can’t put any other non-zero entry anywhere in matrix, because if we put it in some other row, then we will have 4 rows containing non-zeros, if we put it in one of those 3 rows, then we will have more than one non-zero entry in one row, which is not allowed.
So we can fill only “a” non-zero entries if a < b, similarly if b < a, we can put only “b” non-zero entries. So answer is ≤min(a,b), because whatever is less between a and b, we can put atmost that many non-zero entries.
So option (D) is correct.

If 1 and 3 are the eigenvalues of a square matrix A then A3 is equal to
  • a)
    13 (A - I2 )
  • b)
    13A - 12 I2
  • c)
    12 (A - I2)
  • d)
    None of these
Correct answer is option 'B'. Can you explain this answer?

Pankaj Rane answered
Since 1 and 3 are the eigenvalues of A so the characteristic equation of A is
Also, by Cayley–Hamilton theorem, every square matrix satisfies its own characteristic equation so

If the rank of a (5×6) matrix Q is 4, then which one of the following statements is correct?  
  • a)
    Q will have four linearly independent rows and four linearly independent columns  
  • b)
    Q will have four lineally independent rows and five lineally independent columns
  • c)
    QQT will be invertible
  • d)
    QTQ will be invertible 
Correct answer is option 'A'. Can you explain this answer?

Given that rank Q is 4, so it will have 4 linearly independent columns as well as 4 linearly independent rows (∵ row rank of a matrix = column rank of a matrix)

So, A is correct and accordingly B is false.

C is false as order of QQ^T will be 5 x 5 and given that rank of Q is 4 i.e. < 5. So the matrix is QQ^T will be singular and hence not invertible.

Similarly D is false as order of Q^T Q will be 6 x 6 and the matrix is Q^T Q will be singular and hence not invertible.

The sum of the eigenvalues of    is equal to 
  • a)
    18
  • b)
    15
  • c)
    10 
  • d)
    none of these
Correct answer is option 'A'. Can you explain this answer?

Zoya Sharma answered
  • Since the sum of the eigenvalues of an n–square matrix is equal to the trace of the matrix (i.e. sum of the diagonal elements)
  • So, required sum = 8 + 5 + 5  = 18

For the matrix  the eigen value corresponding to the eigenvector 
  • a)
    2
  • b)
    4
  • c)
    6
  • d)
    8
Correct answer is option 'C'. Can you explain this answer?

Prakash Darji answered
Det|A-α |=0 det| 4-α 2| = 0 | 2. 4-α| (4-α )•(4-α) - 4=0 16- 8α + α^2 -4 = 0 α^2 - 8α + 12 =0 (α-6)(α-2)=0α=6 or 2 α is eigen value

The number of linearly independent eigenvectors of 
  • a)
    0    
  • b)
    1    
  • c)
    2    
  • d)
    Infinit e 
Correct answer is option 'B'. Can you explain this answer?

Ravi Singh answered
Number of linear independent vectors is equal to the sum of Geometric Multiplicity of eigen values. Here only eigen value is 2. To find Geometric multiplicity find n-r of (matrix-2I), where n is order and r is rank. Rank of obtained matrix is 1 and n=2 so n-r=1. Therefore the no of linearly independent eigen vectors is 1

Find the Eigenvalues of matrix
  • a)
    8, 2
  • b)
    3, -3 
  • c)
    -3, -5 
  • d)
    5, 0
Correct answer is option 'A'. Can you explain this answer?

Sanya Agarwal answered
A - λI = 0
Now, After taking the determinant:
(4 - λ)2 - 1 = 0
16 + λ2 - 8λ - 1 = 0
λ2 - 8λ + 15 = 0
 - 3) (
λ
 - 5) = 0
λ
 = 3, 5

 Find the rank of the matrix 
  • a)
    2
  • b)
  • c)
    0
  • d)
    3
Correct answer is option 'D'. Can you explain this answer?

Engineers Adda answered
To find out the rank of the matrix first find the |A| 
If the value of the |A| = 0 then the matrix is said to be reduced 
But, as the determinant of A has some finite value, then the rank of the matrix is 3.

Select a suitable figure from the four alternatives that would complete the figure matrix.

  • a)
     
    1
  • b)
     
    2
  • c)
     
    3
  • d)
    4
Correct answer is option 'D'. Can you explain this answer?

Kiran Datta answered
In each row (as well as each column), the third figure is a combination of all the, elements of the first and the second figures

The eigenvalues of
are
  • a)
    3, -5, 37
  • b)
    2, -3, 7
  • c)
    19, -5, -37
  • d)
    -19, 5,  37
Correct answer is option 'D'. Can you explain this answer?

Avinash Sharma answered
The eigenvalues of an upper triangular matrix are simply the diagonal entries of the matrix. Hence 5, -19, and 37 are the eigenvalues of the matrix. Alternately, look at 
Then  = 5,-19,37 are the roots of the equation; and hence, the eigenvalues of [A].

Consider the matrices X (4 × 3), Y (4 × 3) and P (2 × 3). The order or P (XTY)–1PT] T will be 
  • a)
    (2 × 2)
  • b)
    (3 × 3)
  • c)
    (4 × 3)
  • d)
    (3 × 4)
Correct answer is option 'A'. Can you explain this answer?

Suyash Patel answered
X 2 3) and Y (1 2 3). To find the product of X and Y, we need to multiply each element of X with the corresponding element in Y and then sum them up.

The product of X and Y can be calculated as follows:

(4x1) + (2x2) + (3x3) = 4 + 4 + 9 = 17

Chapter doubts & questions for Linear Algebra - Engineering Mathematics 2025 is part of Civil Engineering (CE) exam preparation. The chapters have been prepared according to the Civil Engineering (CE) exam syllabus. The Chapter doubts & questions, notes, tests & MCQs are made for Civil Engineering (CE) 2025 Exam. Find important definitions, questions, notes, meanings, examples, exercises, MCQs and online tests here.

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