Linear Algebra Midterm II Solutions: Standard Matrices, Basis, Linear Dependence - Prof. R, Exams of Linear Algebra

The solutions to problem 1 and problem 3 from the midterm ii exam of math 4305, summer 2011. The problems involve finding the standard matrix of a linear transformation, determining the basis of its image, and investigating the linear dependence of columns. The solutions include step-by-step calculations and explanations.

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2010/2011

Uploaded on 10/31/2011

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Math 4305, Summer 2011,
Midterm II, Practice solutions
Problem 1 Let v= (1,0,1)t. Define the linear transformation T:R3R3
by T(x) = v×x. Where
a1
a2
a3
×
b1
b2
b3
=
a2b3a3b2
a3b1a1b3
a1b2a2b1
.
a) Find the standard matrix Aof T.
Solution A= [a1,a2,a3], where ai=T(ei).
T(e1) =
0
1
0
, T (e2) =
1
0
1
, T (e3) =
0
1
0
.
We thus have
A=
01 0
1 0 1
0 1 0
.
b) Find a basis of im(A).
Solution: We do the interchange of r1and r2, then r3+r2, we thus reach
the REF of A:
1 0 1
01 0
0 0 0
.
Therefore, we know that a basis of im(A) is {a1,a2}.
1
pf3
pf4

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Math 4305, Summer 2011,

Midterm II, Practice solutions

Problem 1 Let v = (1, 0 , 1)t. Define the linear transformation T : R^3 → R^3

by T (x) = v × x. Where

  

a 1 a 2 a 3

   ×

  

b 1 b 2 b 3

   =

  

a 2 b 3 − a 3 b 2 a 3 b 1 − a 1 b 3 a 1 b 2 − a 2 b 1

  .

a) Find the standard matrix A of T.

Solution A = [a 1 , a 2 , a 3 ], where ai = T (ei).

T (e 1 ) =

  

   , T^ (e 2 ) =

  

   , T^ (e 3 ) =

  

  .

We thus have

A =

 

 .

b) Find a basis of im(A).

Solution: We do the interchange of r 1 and r 2 , then r 3 + r 2 , we thus reach the REF of A:

 

 .

Therefore, we know that a basis of im(A) is {a 1 , a 2 }.

c) What’s the dimension of ker(A)?

Solution By the Rank Theorem, we know that

dim ker(A) = 3 − dim im(A) = 1.

Problem 2 Consider an m × n matrix A and an n × m matrix B (with n 6 = m) such that AB = Im. Are the columns of B linearly independent? What about columns of A?

Solution: If columns of B are linearly dependent, so are columns of AB. Thus, if AB = Im, then columns of B are linearly independent. Furthermore, we know that n > m (otherwise, columns of B are linearly dependent). Since A is m × n, columns of A are linearly dependent.

Problem 3 Find a basis B of R^2 such that

[ 1 2

]

B

[ 3 5

] ,

[ 3 4

]

B

[ 2 3

] .

Solution: Let the vectors in B be v 1 and v 2 , and the matrix S = [v 1 , v 2 ]. For any x ∈ R^2 , it is clear that S[x]B = x. Therefore, one reads from the problem that

SA = C

where

A =

( 3 2 5 3

) , C =

( 1 3 2 4

) .

Therefore

Proof Since dimP 2 = 3 and B has 3 vectors, it is sufficient to show that B is linearly independet. Fix the standard basis S = { 1 , t, t^2 }, we check the corresponding coordinate vectors are linearly independent. Let p 1 (t) = 1+t^2 , p 2 (t) = t + t^2 , and p 3 (t) = 1 + 2t + t^2 , we have

A = [[p 1 ]S , [p 2 ]S , [p 3 ]S ] =

 

 .

We easily verify that A is invertible and thus proves that B is linearly independent and so is a basis for P 2.

b) Find the matrix of the linear transformation T (f (t)) = f ′^ − 3 f from P 2 to P 2 withe respect to the basis B found in part (a).

Solution: The desired matrix M can be obtained by

AM = [[T (p 1 )]S , [T (p 2 )]S ], [T (p 3 )]S ] = D. Since T (p 1 ) = −3+2t− 3 t^2 , T (p 2 ) = 1−t− 3 t^2 and T (p 3 ) = − 1 − 4 t− 3 t^2 , thus

M = A−^1 D = A−^1

 

  =

 

− 4 −^12

 .