Midterm 2 Solutions - Linear Algebra | MATH 2270, Exams of Linear Algebra

Material Type: Exam; Class: Linear Algebra; Subject: Mathematics; University: University of Utah; Term: Spring 2009;

Typology: Exams

Pre 2010

Uploaded on 08/31/2009

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Math 2270-2 Midterm 2, February 27, 2009
Solutions
Problem 1 (20 points).Consider the linear transformation from R3
into R3given by the matrix
A=
132
465
798
.
Find:
a) A basis of the kernel of this linear transformation;
b) The nullity of this linear transformation.
Solution: Multiplying the first row by 4 and subtracting from the
second row, and multiplying it by 7 and subtracting from the third row
we get
1 3 2
063
012 6
.
Dividing the second row by 6 and the third by 12 we get
1 3 2
0 1 1
2
0 1 1
2
.
Hence by subtracting the second row from the third, we get:
1 3 2
0 1 1
2
0 0 0
.
Multiplying the second row by 3 and subtracting it from the first one
we get
1 0 1
2
0 1 1
2
0 0 0
.
What is the reduced row echelon form of A. Let
x
y
z
1
pf3
pf4
pf5

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Math 2270-2 Midterm 2, February 27, 2009

Solutions

Problem 1 (20 points). Consider the linear transformation from R^3 into R^3 given by the matrix

A =

Find:

a) A basis of the kernel of this linear transformation; b) The nullity of this linear transformation.

Solution: Multiplying the first row by 4 and subtracting from the second row, and multiplying it by 7 and subtracting from the third row we get (^) 

Dividing the second row by −6 and the third by −12 we get 

Hence by subtracting the second row from the third, we get:  

Multiplying the second row by 3 and subtracting it from the first one we get (^) 

What is the reduced row echelon form of A. Let 

x y z

1

be a vector in the kernel. Then x, y and z satisfy the equations

x +^12 z = 0 y +^12 z = 0

Hence, we have 

x y z

−^12 z −^12 z z

 = −^1

z

and the kernel is spanned by the vector 

In particular, nullity of A is equal to 1.

Problem 2 (20 points). Consider the linear transformation from the first problem. Find: a) A basis of the image of this linear transformation; b) The rank of this linear transformation.

Solution: Since the reduced row echelon form of A is equal to  

we know that the rank of A is 2 and a basis of the image of A is given by the first two columns of A, i.e., by the vectors  

 (^) and

by dividing the second vector by 3 we get a slightly simpler basis  

 (^) and

What is the reduced row echelon form of the augmented matrix. This implies that the solutions are c 1 = − 2 t, c 2 = t and c 3 = t for arbitrary t. It follows that u, v and w are linearly dependent. Moreover, u and v are linearly independent (since c 3 = 0 implies t = 0). Hence w is redundant (since w = 2u − v).

Problem 4 (20 points). Consider the linear space P 2 of all polynomials in t of degree ≤ 2. Show that T (f ) = f ′′^ − 2 f ′^ is a linear transformation from P 2 into P 2. Find the matrix of this linear transformation in the basis { 1 , t, t^2 }.

a) Find the image and the kernel of this linear transformation. b) Is this linear transformation an isomorphism?

(Explain your answer!).

Solution:

We have T (1) = 0, T (t) = −2 and T (t^2 ) = 2 − 4 t. Hence the matrix is equal to

A =

We have

T (a + bt + ct^2 ) = 2c − 2(b + 2ct) = 2(c − b) − 4 ct.

Hence, the kernel consists of all constant polynomials. The image con- sists of all polynomials of degree ≤ 1. Since the kernel is nonzero, this map is not an isomorphism.

Problem 5 (20 points). Consider the linear transformation T from R^2 into R^2 given by the matrix

A =

[

]

Find the matrix B of this linear transformation in the basis

[

]

[

]

a) by direct calculation; b) using the change of basis matrix S.

Solution: a) We have [ 1 − 1 1 1

] [

]

[

]

[

]

[

]

and (^) [ 1 − 1 1 1

] [

]

[

]

[

]

[

]

Hence, we have

B =

[

]

b) On the other hand,

S =

[

]

and

S−^1 =

[

]

Finally, we have

B = S−^1 AS

=

[

] [

] [

]

[

] [

]

[

]