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Math 3130: Introduction to Linear Algebra, Fall 2016


Homework


Most or all sections of the book have a list of practice problems immediately preceding the exercises for the section. You should try to solve all these practice problems, since they cover the most fundamental information of the section. The solutions to the practice problems may be found at the end of the list of exercises for the section.

The book also contains solutions to odd numbered exercises, so these should be considered to be practice problems too. (Try them!)

The problem numbers refer to the 5th edition of the book!





Assignment
Assigned
Due
Problems
HW1 8/24/16
8/31/16
Read Sections 1.1-1.3.

Section 1.1: 4, 12, 16, 18, 20
Section 1.2: 4, 14, 16

HW2 9/1/16
9/7/16
Read Sections 1.4, 2.1

Section 1.4: 10, 12, 14
Section 2.1: 2, 6, 10, 12, 20

HW3 9/8/16
9/14/16
Read Sections 1.5, 1.7.

Section 1.5: 8, 20, 22
Section 1.7: 2, 10, 32

Extra:
1. Let $A$ be the $3\times 3$ zero matrix. Express the solution to $A{\bf x}={\bf 0}$ in parametric vector form.
2. Explain why, if $A$ is an $m\times n$ matrix and $m\lt n$, the columns of $A$ must be dependent.

HW4 9/16/16
9/21/16
Read Sections 1.8, 1.9.

Section 1.8: 18, 30
Section 1.9: 4, 6, 8, 10, 12, 30

Extra: 1. If ${\bf p}$ and ${\bf d}$ are vectors in $\mathbb R^n$, and ${\bf d}\neq {\bf 0}$, then the set of all vectors of the form ${\bf x}={\bf p}+t{\bf d}$, $t\in \mathbb R$, is a line in ${\mathbb R}^n$. If ${\bf d}={\bf 0}$, then this set is just the singleton $\{{\bf p}\}$.
Show that the image of this line under a linear transformation is either a line or a singleton.

HW5 9/21/16
9/28/16
Read Sections 1.6, 1.10, 2.2.

Section 1.6: 6
Section 2.1: 26, 28
Section 2.2: 2, 16, 20, 22, 24

Extra:
1. Show that if $A$ has a left inverse, then $A^t$ has a right inverse.

HW6 9/29/16
10/5/16
Read Sections 2.3, 2.8, 2.9.

Section 2.3: 8, 18
Section 2.8: 2, 22(a)(b)(d), 24
Section 2.9: 14, 18(a)(c)(d)

Extra:
1. Explain why $\mathbb R^4$ has no $5$-dimensional subspace.

HW7 10/6/16
10/12/16
Read Sections 3.1, 3.2, 3.3.

Section 3.1: 4, 14, 16, 40
Section 3.2: 8, 22, 24, 34
Section 3.3: 22

HW8 10/20/16
10/28/16
Read Sections 4.1, 4.2, 4.3, 4.4. (Much of this reviews material from Chapter 2 in the new setting of abstract vector spaces.) Please don't overlook the nice table of information at the top of page 206.

Section 4.1: 22, 24, 28
Section 4.2: 26
Section 4.3: 22
Section 4.4: 14, 16, 32
Extra:
1. Find a basis for the kernel of the linear transformation $L\colon \mathbb P_2\to \mathbb R^2\colon p(t)\mapsto [p(0)\;p'(0)]^T$.
(The kernel of a linear transformation $L$ is the set of all $\mathbf x$ such that $L({\mathbf x}) = {\mathbf 0}$ Observe that any correct answer to this problem will be a set of polynomials.)

Practice
only


Read Sections 4.5, 4.6, 4.7.

Section 4.5: 32
Section 4.6: 4, 8, 30
Section 4.7: 6, 8
Chapter 4 Supplementary Exercises: 4, 10, 12
Extra:
1. Suppose that $\mathbb V\leq \mathbb R^3$ is spanned by ${\mathcal B} = \left( \left[\begin{array}{c}1\\2\\3\end{array}\right], \left[\begin{array}{c}4\\5\\6\end{array}\right] \right)$ and $\mathbb W\leq \mathbb R^3$ is spanned by ${\mathcal C} = \left(\left[\begin{array}{c}1\\2\\4\end{array}\right], \left[\begin{array}{c}1\\3\\9\end{array}\right] \right)$. Find bases for $\mathbb V+\mathbb W$ and $\mathbb V\cap\mathbb W$.

HW9 11/2/16
11/9/16
Read Sections 5.1, 5.2, 5.3.

Section 5.1: 8, 16, 22(a)(b)(d)(e), 30
Section 5.2: 20
Section 5.3: 8, 12

Extra:
1. Show that if $\lambda$ is an e-value for $A$ and $k$ is an integer, then $\lambda^k$ is an e-value for $A^k$.

2. Suppose that $A$ is a block upper triangular matrix with diagonal blocks $A_1,\ldots,A_k$. Show that the characteristic polynomial of $A$ is the product of the characteristic polynomials of the $A_i$'s.

HW10 11/11/16
11/16/16
Read Sections 5.4, 5.5.

Section 5.4: 14, 19, 20, 22
Section 5.5: 2
Extra:
1. Suppose that $A$ is a $2\times 2$-matrix and that $\det(A-I) = -16$ and $\det(A-2I) = -15$. What are the e-values of $A$?

2. Let $\mathbb P_n(t)$ be the space of polynomials of degree at most $n$ in the variable $t$. Let $D\colon\mathbb P_3(t)\to \mathbb P_3(t)\colon f\mapsto f'$ be the operation of differentiation. Find the characteristic polynomial, e-values, and e-spaces of $D$.

3. Let $T\colon M_{2\times 2}(\mathbb R)\to M_{2\times 2}(\mathbb R)\colon M\mapsto M^T$ be the operation of transpose. Find the characteristic polynomial, e-values, and e-spaces of $T$.

4. Let $E(t)$ be the subspace of $\mathbb P_3(t)$ consisting of polynomials whose monomials have even exponent (like $1$, $t^2$, $t^4$, etc) and let $O(t)$ be the subspace consisting of polynomials whose monomials have odd exponent (like $t$, $t^3$, etc). Show that $\mathbb P_n(t) = E(t) \oplus O(t)$. What are the dimensions of $\mathbb P_n(t)$, $E(t)$ and $O(t)$ when $n=100$?

5. Suppose that $T\colon V\to V$ is a linear transformation defined on a finite dimensional vector space $V$ and that $T$ has an eigenvalue $\lambda$ whose associated eigenspace is all of $V$ (i.e. $V_{\lambda} = V$). What are the possible matrices ${}_{\mathcal B}[T]_{\mathcal B}$ for different bases ${\mathcal B}$?

HW11 11/18/16
11/30/16
Read Sections 5.7

Section 5.5: 2
Chapter 5, Supplementary Problems: 6, 10
Extra:
1. What is the minimal polynomial of the $3\times 3$ matrix of all $1$'s? Does your answer suggest that the matrix is diagonalizable or nondiagonalizable?

2. How is the minimal polynomial of $A$ related to the minimal polynomial of $A-I$?

3. Show that if $A$ is diagonalizable, then $A-I$ is diagonalizable.



Read Sections 6.1-6.3, 6.5