A square matrix A is called singular if
A
det(A) ≠ 0
B
det(A) = 0
C
A is diagonal
D
A is identity
Analysis & Theory
If determinant of A = 0, the matrix is singular.
A square matrix A is non-singular if
A
det(A) = 0
B
det(A) ≠ 0
C
A is zero matrix
D
A is symmetric
Analysis & Theory
If determinant ≠ 0, the matrix is non-singular.
Which of the following is true for a non-singular matrix?
A
It has no inverse
B
It has an inverse
C
It must be diagonal
D
It is always symmetric
Analysis & Theory
Non-singular matrices are invertible.
Which of the following is true for a singular matrix?
A
It is always diagonal
B
It has no inverse
C
Its determinant is non-zero
D
It is identity matrix
Analysis & Theory
Singular matrices do not have an inverse.
If det(A) = 0, then A is called
A
Non-singular
B
Singular
C
Identity
D
Orthogonal
Analysis & Theory
Determinant zero implies matrix is singular.
If det(A) ≠ 0, then A is called
A
Non-singular
B
Singular
C
Diagonal
D
Zero matrix
Analysis & Theory
Non-singular matrices have non-zero determinant.
The product of two non-singular matrices is
A
Always singular
B
Always non-singular
C
Zero matrix
D
Identity
Analysis & Theory
Product of two non-singular matrices is non-singular because det(AB) = det(A)·det(B) ≠ 0.
The determinant of a singular matrix is
A
Always non-zero
B
Always zero
C
Always one
D
Unpredictable
Analysis & Theory
By definition, singular matrix has determinant zero.
The determinant of a non-singular matrix is
A
Zero
B
Non-zero
C
Negative only
D
One only
Analysis & Theory
Non-singular matrices have non-zero determinants.
If A is a non-singular matrix, then system of equations AX = B has
A
No solution
B
Unique solution
C
Infinite solutions
D
Only trivial solution
Analysis & Theory
For non-singular A, inverse exists, so AX = B has a unique solution X = A⁻¹B.