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  1. Asked: 3 years agoIn: Matrices

    Find the (adj A), if

    A = \(\rm \begin{bmatrix} 3& 7& 1 \\ 2& 1& 8\\ 4& 5& 0\end{bmatrix}\)


    1. \(\rm \begin{bmatrix} -40& 32& 55 \\ 5& -4& 13\\ 55& -22& -11\end{bmatrix}\)
    2. \(\rm \begin{bmatrix} 3& 7& 1 \\ 2& 1& 8\\ 4& 5& 0\end{bmatrix}\)
    3. \(\rm \begin{bmatrix} -40& 32& 6 \\ 5& -4& 13\\ 55& -22& -11\end{bmatrix}\)
    4. \(\rm \begin{bmatrix} -40& 5& 55\\ 32& -4& -22\\ 6& 13& -11\end{bmatrix}\)

    4dd25
    Added an answer about 3 years ago

    Correct Answer - Option 4 : \(\rm \begin{bmatrix} -40& 5& 55\\ 32& -4& -22\\ 6& 13& -11\end{bmatrix}\)Concept:If matrix A = [aij]The adj A matrix is the transpose of the matrix [Aij] is the cofactor of the element aij.Calculation:A = \(\rm \begin{bmatrix} 3& 7& 1 \\ 2Read more

    Correct Answer – Option 4 : \(\rm \begin{bmatrix} -40& 5& 55\\ 32& -4& -22\\ 6& 13& -11\end{bmatrix}\)

    Concept:

    If matrix A = [aij]

    The adj A matrix is the transpose of the matrix [Aij] is the cofactor of the element aij.

    Calculation:

    A = \(\rm \begin{bmatrix} 3& 7& 1 \\ 2& 1& 8\\ 4& 5& 0\end{bmatrix}\) 

    Cof(a11) = 0 – 40 = -40

    Cof(a12) = -(0 – 32) = 32

    Cof(a13) = 10 – 4 = 6

    Cof(a21) = -(0 – 5) = 5

    Cof(a22) = 0 – 4 = -4

    Cof(a23) = -(15 – 28) = 13

    Cof(a31) = 56 – 1 = 55

    Cof(a32) = -(24 – 2) = -22

    Cof(a33) = 3 – 14 = -11

    cof A = \(\rm \begin{bmatrix} -40& 32& 6 \\ 5& -4& 13\\ 55& -22& -11\end{bmatrix}\)

    Adj A = (cof A)T = \(\rm \begin{bmatrix} -40& 32& 6 \\ 5& -4& 13\\ 55& -22& -11\end{bmatrix}^T\)

    ⇒ Adj A = \(\rm \begin{bmatrix} -40& 5& 55\\ 32& -4& -22\\ 6& 13& -11\end{bmatrix}\)

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  2. Asked: 3 years agoIn: Matrices

    If the matrix \(\rm A = \left [ \begin{array}{cc} \alpha & \beta \\ \beta & \alpha \end{array}\right ]\) is such that A2 = I, then which one of the following is correct? 
    1.  α = 0, β = 1 OR  α = 1, β = 0
    2.  α = 1, β = 1 OR  α = 1, β = 0
    3.  α ≠  1, β = 0
    4. α = β = 0

    ebfb1
    Added an answer about 3 years ago

    Correct Answer - Option 1 :  α = 0, β = 1 OR  α = 1, β = 0Calculation:Here, \(\rm A = \left [ \begin{array}{cc} α & β \\ β & α \end{array}\right ]\)\(\begin{array}{l} \therefore \rm A^{2}=A=\left[\begin{array}{ll} α & β \\ β & α \end{array}\right]\left[\begin{array}{ll} α & β \\Read more

    Correct Answer – Option 1 :  α = 0, β = 1 OR  α = 1, β = 0

    Calculation:

    Here, \(\rm A = \left [ \begin{array}{cc} α & β \\ β & α \end{array}\right ]\)

    \(\begin{array}{l} \therefore \rm A^{2}=A=\left[\begin{array}{ll} α & β \\ β & α \end{array}\right]\left[\begin{array}{ll} α & β \\ β & α \end{array}\right] \\ \end{array}\)

    \(=\left[\begin{array}{l} α^{2}+β^{2} & 2 α β\\ 2 α β &α^{2}+β^{2} \end{array}\right] \\ \text { Now } \rm A^{2}=I \\ \)

    \(\Rightarrow \left[\begin{array}{l} α^{2}+β^{2} & 2 α β \\ 2 α β& α^{2}+β^{2} \end{array}\right]=\left[\begin{array}{ll} 1 & 0 \\ 0 & 1 \end{array}\right] \\ \\ \Rightarrow α^{2}+β^{2}=1, \quad α β=0\)
    So, α = 0, β = 1 OR  α = 1, β = 0 

    Hence, option (1) is correct. 

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  3. Asked: 3 years agoIn: Matrices

    The inverse of the matrix \(\rm \begin{bmatrix} 2+3i & -i\\ i & 2-3i \end{bmatrix}\)is
    1. \( \frac{1}{12}\begin{bmatrix} 2-3i & i\\ -i & -2+3i \end{bmatrix}\)
    2. \( \frac{1}{12}\begin{bmatrix} 2-3i & i\\ -i & 2+3i \end{bmatrix}\)
    3. \( \frac{1}{12}\begin{bmatrix} 2+3i & i\\ -i & 2-3i \end{bmatrix}\)
    4. \( \frac{1}{12}\begin{bmatrix} 2-3i & -i\\ i & 2+3i \end{bmatrix}\)

    a3e7c
    Added an answer about 3 years ago

    Correct Answer - Option 2 : \( \frac{1}{12}\begin{bmatrix} 2-3i & i\\ -i & 2+3i \end{bmatrix}\)Concept:For a 2 x 2 matrix there is a short-cut formula for inverse as given below\(\rm {\begin{bmatrix} a & & b\\ c& & d \end{bmatrix}}^{-1} = \frac{1}{(ad-bc)}\begin{bmatrix} dRead more

    Correct Answer – Option 2 : \( \frac{1}{12}\begin{bmatrix} 2-3i & i\\ -i & 2+3i \end{bmatrix}\)

    Concept:

    For a 2 x 2 matrix there is a short-cut formula for inverse as given below

    \(\rm {\begin{bmatrix} a & & b\\ c& & d \end{bmatrix}}^{-1} = \frac{1}{(ad-bc)}\begin{bmatrix} d & & -b\\ -c& & a \end{bmatrix}\)

    Calculation:

    A we know that inverse of matrix \(\rm {\begin{bmatrix} a & & b\\ c& & d \end{bmatrix}}^{-1} = \frac{1}{(ad-bc)}\begin{bmatrix} d & & -b\\ -c& & a \end{bmatrix}\)

    ⇒ \({\begin{bmatrix} 2+3i & -i\\ i & 2-3i \end{bmatrix}}^{-1}= \frac{1}{(2+3i)(2-3i)-1}\begin{bmatrix} 2-3i & i\\ -i & 2+3i \end{bmatrix}\)

    ⇒ \({\begin{bmatrix} 2+3i & -i\\ i & 2-3i \end{bmatrix}}^{-1}= \frac{1}{4+9-1}\begin{bmatrix} 2-3i & i\\ -i & 2+3i \end{bmatrix}\)

    ⇒ \({\begin{bmatrix} 2+3i & -i\\ i & 2-3i \end{bmatrix}}^{-1}= \frac{1}{12}\begin{bmatrix} 2-3i & i\\ -i & 2+3i \end{bmatrix}\)

    Hence, option 2 is correct.

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  4. Asked: 3 years agoIn: Matrices

    If A and B are symmetric matrices of the same order, then (AB’ – BA’) is:
    1. Skew symmetric matrix
    2. Symmetric matrix
    3. Null matrix
    4. Identity matrix

    c9a3a
    Added an answer about 3 years ago

    Correct Answer - Option 1 : Skew symmetric matrixConcept:We have various matrix identities as,For symmetric matrices, A = A' and B = B'For skew-symmetric matrices, A = - A'(A ± B)' = A' ± B'(AB)' = B'A' Calculation:A and B are symmetric matricesAs we know that for symmetric matrices, we have A = A'Read more

    Correct Answer – Option 1 : Skew symmetric matrix

    Concept:

    We have various matrix identities as,

    • For symmetric matrices, A = A’ and B = B’
    • For skew-symmetric matrices, A = – A’
    • (A ± B)’ = A’ ± B’
    • (AB)’ = B’A’

     

    Calculation:

    A and B are symmetric matrices

    As we know that for symmetric matrices, we have A = A’ and B = B’

    (AB’ – BA’) = AB – BA

    ∵ (A ± B)’ = A’ ± B’

    (AB – BA)’ = (AB)’ – (BA)’

    ∵ (AB)’ = B’A’

    ⇒ (AB – BA)’ = B’A’ – A’B’

    ∵ A = A’ and B = B

    ⇒ (AB – BA)’ = BA – AB

    ⇒ (AB – BA)’ = – (AB – BA)

    Since for skew-symmetric matrices, A = – A’

    Hence (AB’ – BA’) is Skew symmetric matrix.

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  5. Asked: 3 years agoIn: Matrices

    Let \(\Delta = \begin{vmatrix} Ax & x^2 & 1 \\\ By & y^2 & 1 \\\ Cz & z^2 & 1 \end{vmatrix}\) and \(\Delta_1 = \begin{vmatrix} A & B & C \\\ x & y & z \\\ zy & zx & xy \end{vmatrix}\), then
    1. Δ1 = -Δ 
    2. Δ1 ≠ Δ
    3. Δ1 – Δ = 0
    4. Δ1 = Δ = 0

    83689
    Added an answer about 3 years ago

    Correct Answer - Option 3 : Δ1 - Δ = 0Explanation:\(Δ = \begin{vmatrix} Ax & x^2 & 1 \\\ By & y^2 & 1 \\\ Cz & z^2 & 1 \end{vmatrix}\)  and  \(Δ_1 = \begin{vmatrix} A & B & C \\\ x & y & z \\\ zy & zx & xy \end{vmatrix}\)Calculating the determinant of Read more

    Correct Answer – Option 3 : Δ1 – Δ = 0

    Explanation:

    \(Δ = \begin{vmatrix} Ax & x^2 & 1 \\\ By & y^2 & 1 \\\ Cz & z^2 & 1 \end{vmatrix}\)  and  \(Δ_1 = \begin{vmatrix} A & B & C \\\ x & y & z \\\ zy & zx & xy \end{vmatrix}\)

    Calculating the determinant of Δ1 :

    \(Δ_1 = \begin{vmatrix} A & B & C \\\ x & y & z \\\ zy & zx & xy \end{vmatrix}\)

    Δ1 = A × (x × y2 – x × z2) – B × (x2 × y – z2 × y) + C × (x2 × z – y2 × z)

         = A × x (y2 – z2) – B × y (x2 – z2) + C × z (x2 – y2)………….(1)

    Calculating the determinant of Δ about first column:

    \(Δ = \begin{vmatrix} Ax & x^2 & 1 \\\ By & y^2 & 1 \\\ Cz & z^2 & 1 \end{vmatrix}\)

    Δ = A × x (y2 – z2) – B × y (x2 – z2) + C × z (x2 – y2)…………(2)

    If we subtract (1) and (2) 

    Δ1 – Δ = 0

    Hence option 3 is the correct answer.

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  6. Asked: 3 years agoIn: Matrices

    A square matrix A satisfies A2=I-A , where I is the identity matrix. If An =5A – 3I, find the value of n.

    2e126
    Added an answer about 3 years ago

    The value of n will be 5Explanation:We know that I x A = AA2 = I - AA3 = A(I - A) = IA - A2 = A - (I - A) = 2A - I A4 = A x A3 = A(2A - I) = 2A2 -A = 2(I - A) - A = 2I - 3AA5 = A(2I - 3A) = 2A - 3A2 = 2A - 3(I-A) = 5A - 3IThus, A5 = 5A - 3I

    The value of n will be 5

    Explanation:

    We know that I x A = A

    A2 = I – A
    A3 = A(I – A) = IA – A2 = A – (I – A) = 2A – I 
    A4 = A x A3 = A(2A – I) = 2A2 -A = 2(I – A) – A = 2I – 3A
    A5 = A(2I – 3A) = 2A – 3A2 = 2A – 3(I-A) = 5A – 3I

    Thus, A5 = 5A – 3I

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  7. Asked: 3 years agoIn: Matrices

    Consider the following statements in respect of a square matrix A and its transpose AT :

    1. A + AT is always symmetric.

    2. A – AT is always anti-symmetric.

    Which of the statements given above is / are correct?


    1. 1 only
    2. 2 only
    3. Both 1 and 2
    4. Neither 1 nor 2

    b67b2
    Added an answer about 3 years ago

    Correct Answer - Option 3 : Both 1 and 2Concept:Symmetric matrix is a square matrix that is equal to its transpose.i.e. A = AT.A skew-symmetric (or antisymmetric or antimetric) matrix is a square matrix whose transpose equals its negative.i.e.  AT = - A(A + B)T = (A)T  + (B)T (AT)T  = ACalculations:Read more

    Correct Answer – Option 3 : Both 1 and 2

    Concept:

    Symmetric matrix is a square matrix that is equal to its transpose.

    i.e. A = AT.

    A skew-symmetric (or antisymmetric or antimetric) matrix is a square matrix whose transpose equals its negative.

    i.e.  AT = – A

    (A + B)T = (A)T  + (B)T 

    (AT)T  = A

    Calculations:

    Given, A is any square matrix and AT is transpose matrix A

    Consider the statement “A + AT is always symmetric.”

    We know that “a symmetric matrix is a square matrix that is equal to its transpose.“

    i.e. A = AT.

    Consider, the matrix A + AT ….(1)

    Taking transpose of the matrix A + AT 

    (A + AT)T = (A)T  + (AT)T 

    ⇒(A + AT)T = (A)T + A

    ⇒(A + AT)T = A + (A)T 

    ⇒ A + AT is symmetric.

    Hence, the statement “A + AT is always symmetric is true.

     

    Consider the statement “A – AT is always anti-symmetric” 

    A skew-symmetric (or antisymmetric or antimetric) matrix is a square matrix whose transpose equals its negative.

    i.e.  AT = – A

    Consider, the matrix A – AT ….(1)

    Taking transpose of the matrix A – AT 

    (A – AT)T = (A)T  – (AT)T 

    ⇒(A – AT)T = (A)T – A

    ⇒(A – AT)T = – (A – AT)

    ⇒ A – AT is symmetric.

    Hence, the statement “A – AT is always symmetric is true.

    Hence, the following statements in respect of a square matrix A and its transpose AT :

    1. A + AT is always symmetric.

    2. A – AT is always anti-symmetric.

    both are correct

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  8. Asked: 3 years agoIn: Matrices

    If \(\begin{bmatrix} 1 & -3 & 2 \\\ 2 & -8 & 5 \\\ 4 & 2 & λ \end{bmatrix}\) is not an invertible matrix, then what is the value of λ ?
    1. -1
    2. 0
    3. 1
    4. 2

    93213
    Added an answer about 3 years ago

    Correct Answer - Option 3 : 1Concept:If the matrix A is not an invertible matrix then | A | = 0If the matrix A is the non-singular matrix then | A | ≠ 0  Calculations:Given, A = \(\begin{bmatrix} 1 & -3 & 2 \\\ 2 & -8 & 5 \\\ 4 & 2 & λ \end{bmatrix}\)is not an invertible matrRead more

    Correct Answer – Option 3 : 1

    Concept:

    If the matrix A is not an invertible matrix then | A | = 0

    If the matrix A is the non-singular matrix then | A | ≠ 0 

     

    Calculations:

    Given, A = \(\begin{bmatrix} 1 & -3 & 2 \\\ 2 & -8 & 5 \\\ 4 & 2 & λ \end{bmatrix}\)is not an invertible matrix

    As we know, If the matrix A is non invertible matrix then | A | = 0

    ⇒ \(\begin{vmatrix} 1 & -3 & 2 \\\ 2 & -8 & 5 \\\ 4 & 2 & λ \end{vmatrix}\) = 0

    ⇒ 1\(\rm (-8\lambda – 10)+3(2\lambda-20)+2(4+32)\) = 0

    ⇒ \(\rm -8\lambda – 10+6\lambda-60+72 = 0\)

    ⇒\(\rm -2\lambda +2 = 0\)

    ⇒\(\rm \lambda = 1\)

    Hence, If \(\begin{bmatrix} 1 & -3 & 2 \\\ 2 & -8 & 5 \\\ 4 & 2 & λ \end{bmatrix}\) is not an invertible matrix, then the value of λ is 1.

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  9. Asked: 3 years agoIn: Matrices

    Consider the following statements:

    1. If A′ = A; then A is a singular matrix, where A′ is the transpose of A.

    2. If A is a square matrix such that A3 = I, then A is non-singular.

    Which of the statements given above is/are correct ?


    1. 1 only 
    2. 2 only 
    3. Both 1 and 2
    4. Neither 1 nor 2

    8af42
    Added an answer about 3 years ago

    Correct Answer - Option 2 : 2 only Concept:A matrix is singular if and only if its determinant is zero. Calculation:If A′ = A; where A′ is the transpose of A then |A| = |A'|But it is not necessary that |A| = 0, so A is not a  singular matrix.Hence, Statement 1 is wrong. Given, A3 = ITaking determinaRead more

    Correct Answer – Option 2 : 2 only 

    Concept:

    A matrix is singular if and only if its determinant is zero.

     

    Calculation:

    If A′ = A; where A′ is the transpose of A then |A| = |A’|

    But it is not necessary that |A| = 0, so A is not a  singular matrix.

    Hence, Statement 1 is wrong.

     

    Given, A3 = I

    Taking determinants both sides, we get

    ⇒|A3 | = |I| = 1

    ⇒ |A| = 1

    Here, |A|≠ 0 so, A is a non-singular matrix

    Hence, option (2) is correct.  

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  10. Asked: 3 years agoIn: Matrices

    Find the inverse of the matrix \(\begin{bmatrix} 1& -3 \\ 4& 2 \end{bmatrix}\)
    1. \({1\over14}\begin{bmatrix} 2& -3 \\ 4& -1 \end{bmatrix}\)
    2. \({1\over14}\begin{bmatrix} 2& 3 \\ -4& 1 \end{bmatrix}\)
    3. \({1\over14}\begin{bmatrix} 2& -3 \\ -4& 1 \end{bmatrix}\)
    4. \({1\over14}\begin{bmatrix} 2& 3 \\ 4& 1 \end{bmatrix}\)

    538a2
    Added an answer about 3 years ago

    Correct Answer - Option 2 : \({1\over14}\begin{bmatrix} 2& 3 \\ -4& 1 \end{bmatrix}\)Concept: For any matrix A, If matrix A = [aij]A-1 = \(\rm \text{(adj A)}\over|A|\)The adj A matrix is the transpose of the matrix [Aij] is the cofactor of the element aij.Calculation:A = \(\begin{bmatrix} 1Read more

    Correct Answer – Option 2 : \({1\over14}\begin{bmatrix} 2& 3 \\ -4& 1 \end{bmatrix}\)

    Concept: 

    For any matrix A, If matrix A = [aij]

    A-1 = \(\rm \text{(adj A)}\over|A|\)

    The adj A matrix is the transpose of the matrix [Aij] is the cofactor of the element aij.

    Calculation:

    A = \(\begin{bmatrix} 1& -3 \\ 4& 2 \end{bmatrix}\) = [aij]

    |A| = \(\begin{vmatrix} 1& -3 \\ 4& 2 \end{vmatrix}\) 

    ⇒ |A| = 2 × 1 – (-3) × 4

    ⇒ |A| = 14

    Now, finding cofactor of matrix

    a11 = 1, cof(a11) = 2

    a12 = -3, cof(a12) = -4

    a21 = 4, cof(a21) = 3

    a22 = 2, cof(a22) = 1

    Cof(A) = \(\begin{bmatrix} 2& -4 \\ 3& 1 \end{bmatrix}\)

    adj(A) = [cof(A)]T 

    adj(A) = \(\begin{bmatrix} 2& 3 \\ -4& 1 \end{bmatrix}\)

    A-1 = \(\rm \text{(adj A)}\over|A|\) 

    ⇒ A-1 = \(\boldsymbol{{1\over14}\begin{bmatrix} 2& 3 \\ -4& 1 \end{bmatrix}}\)

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