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Math 314 Final Exam Spring, 1996

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<strong>Math</strong> 309<br />

Sample <strong>Final</strong> <strong>Exam</strong><br />

1.(20 pts) State clearly and concisely the definition of each of the following concepts.<br />

(a) The set of vectors { , ,..., }<br />

n<br />

v1 v2<br />

vn<br />

⊆ R is linearly dependent.<br />

(b) λ is an eigenvalue of the ( nxn) matrix A.<br />

(c)<br />

The matrix<br />

nxn<br />

A∈R is diagonalizable.<br />

(d)<br />

A is row equivalent to B, where A and B are (mxn) matrices.<br />

2.(12 pts) Find a basis for the subspace S P 3<br />

, where S = p∈ P3 p′ (1) = 0 . Here P n<br />

denotes<br />

the vector space of all polynomials of degree less than n.<br />

⊆ { }


⎡1 2 −1 1⎤<br />

3.(24 pts) Given that A =<br />

⎢<br />

2 4 −3 0<br />

⎥<br />

has row echelon form<br />

⎢<br />

⎥<br />

U<br />

⎢⎣1 2 1 5⎥⎦<br />

⎡1 2 −1 1⎤<br />

=<br />

⎢<br />

0 0 1 2<br />

⎥<br />

⎢ ⎥<br />

⎢⎣<br />

0 0 0 0⎥⎦<br />

(a) Find a basis for the null space of A.<br />

(b) Find a basis for the range of A.<br />

(c) Find a basis for the row space of A.<br />

(d) Determine rank ( A)<br />

.<br />

4.(28 pts) True or false. Please explain your answer.


(a) If A = BC where B is nonsingular, then rank( A) = rank( C)<br />

.<br />

4<br />

(b) If A is (4x3) and rank( A) = 3 , then Ax= b is solvable for any b∈<br />

R .<br />

(c)<br />

There exist (2x2) matrices A and B such that both A and B are singular, but<br />

AB is nonsingular.<br />

k<br />

(d) If A is an (nxn) matrix for which A = 0 for some k >1, then A is singular.<br />

5.(20 pts) For each of the following, if U is a subspace of V, verify the subspace criteria. If U is<br />

not a subspace of V, explain precisely why not.<br />

nxn<br />

(a) U = all (nxn) nonsingular matrices, V = R .<br />

nxn<br />

(b) U = all (nxn) symmetric matrices, V = R .


6.(10 pts) Let { x , , 1<br />

xn}<br />

{ x x }<br />

be an orthonormal set in an inner product space V. Prove that<br />

, , 1<br />

<br />

n<br />

is linearly independent.<br />

nxn<br />

7.(10 pts) Let A,<br />

B∈R . If A is diagonalizable and B is similar to A, prove that B is also<br />

diagonalizable.<br />

8.(16 pts) Which of the following matrices are diagonalizable and which are not. Please give


oth an answer and a reason.<br />

(a)<br />

⎡2 2 1 ⎤<br />

⎢<br />

0 1 2<br />

⎥<br />

⎢ ⎥<br />

⎢⎣0 0 −1⎥⎦<br />

(b)<br />

⎡2 −1⎤<br />

⎢<br />

0 2<br />

⎥<br />

⎣ ⎦<br />

3<br />

9.(16 pts) Consider the linear transformation L:<br />

P → P<br />

4 defined by L( p)( x) = xp( x)<br />

. Find the<br />

matrix which represents L relative to the bases { 2<br />

2 3<br />

1,1 −x,1<br />

− x+ x } in P<br />

3<br />

and { 1, x, x , x } in P 4<br />

.


10.(20 pts) Given the data, find the equation of the line y= a0 + a1x<br />

which best fits the data in<br />

the least squares sense.<br />

x 0 3 6<br />

y 1 4 5<br />

⎡1 1 1⎤<br />

11.(14 pts) Given A =<br />

⎢<br />

1 0 1<br />

⎥<br />

, factor A into a product QR, where Q is orthogonal and R is<br />

⎢⎢ ⎥<br />

⎣0 1 1 ⎥ ⎦<br />

upper triangular and nonsingular.


⎡2 −3⎤<br />

12.(10 pts) The matrix A = ⎢ has eigenvalues<br />

⎣2 −5<br />

⎥ λ<br />

1<br />

= 1 and λ<br />

2<br />

= − 4 . Find the<br />

⎦<br />

corresponding eigenvectors.

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