- Type
- Final term past paper
- Course
- MTH501 Linear Algebra
- Size
- PDF 1.4 MB
- Updated
- 23 Oct 2026
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Q1. Which statement about the General Least Square Method is true?
- Solution obtained by this method is always Unique.
- This is a numerical method for the solution of system of Linear Equations.
- This method find an X that make Ax as close possible to the b.
- This method gives us exact solution of the System.
2. Let v = (1, -2, 2, 0). The unit vector in the same
, , , 0
- 1 2 2 , 0 1 2 2 1
- Let u = (3, -2), v= (4, 5). For the weighted Euclidean inner product (u, v) = 4u1v1 + 5 u2v2 (v, u) = 2
- -2
3
- -3
- Attractor
8. Suppose that A =
0.5
0.6 has eigenvalues 0.8 and
-0.3 1.4
1.1. then 0rigin is a
- Repellor
- Attractor
- if A is an m x n matrix with linearly independent column vector, then A can be factored as
A= QR
Where Q is an m X n matrix orthonormal column vector ,and R is an n x m.
- Upper triangular matrix
- Invertible matrix
- Invertible lower triangular matrix
- invertible Upper triangular matrix
- The matrix equation AT A x^ = AT b represent a system of liner equation Commonly referred to as the
- Normal equation for x
- Normal equation for X^
- Normal equation for A
- Normal equation for b
- By the best Approximation theorem , the distance from y to W is ||y – Y^|| , where Y^=
- Projw Y^
- Projwy is
- projy W
- ||u + v + w|| ||u|| + ||v|| +||w|| for all vectors u, v and w in an inner product space.
- True
- False
13. The dominate for the matrix A =
- =1 0 0 0 1 0 0 -3 0 0
- = -1
- = 0
- A square matrix A I invertible if and only if and only is X = 0 is not an Eigen Value of A
- True
- False
- A square matrix with orthogonal columns ----------- -------matrix.
- Is an orthogonal
- May be an orthogonal
- May not be an orthogonal
- Is not an orthogonal
- if two row are orthogonal , they are -------------- --.
- Linearly independent
- Linearly Dependent
- = -3
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