Math 550 Notes. Chapter 2. Jesse Crawford. Department of Mathematics Tarleton State University. Fall 2010

Size: px
Start display at page:

Download "Math 550 Notes. Chapter 2. Jesse Crawford. Department of Mathematics Tarleton State University. Fall 2010"

Transcription

1 Math 550 Notes Chapter 2 Jesse Crawford Department of Mathematics Tarleton State University Fall 2010 (Tarleton State University) Math 550 Chapter 2 Fall / 20

2 Linear algebra deals with finite dimensional vector spaces. Reminder F denotes R or C. V is a vector space over F. (Tarleton State University) Math 550 Chapter 2 Fall / 20

3 Outline 1 Span and Linear Independence 2 Bases 3 Dimension (Tarleton State University) Math 550 Chapter 2 Fall / 20

4 Linear Combinations and Span Definition Let (v 1,..., v m ) be a list of vectors in V. A linear combination of (v 1,..., v m ) is a vector of the form where a 1,..., a m F. a 1 v a m v m, The set of all such linear combinations is span(v 1,..., v m ). span(v 1,..., v m ) = {a 1 v a m v m a 1,..., a m F} span(v 1,..., v m ) is the smallest subspace of V containing v 1,..., v m. Special case: span() = {0}. (Tarleton State University) Math 550 Chapter 2 Fall / 20

5 Finite Dimensional Spaces Definition If span(v 1,..., v m ) = V, we say (v 1,..., v m ) spans V and that V is finite dimensional. Example In F n, define e j to be the vector whose jth coordinate is 1 and whose other coordinates are 0. e 1 = (1, 0,..., 0) e 2 = (0, 1,..., 0). e n = (0, 0,..., 1) Then F n = span(e 1,..., e n ), so F n is finite dimensional. (e 1,..., e n ) is called the standard basis for F n. (Tarleton State University) Math 550 Chapter 2 Fall / 20

6 Example Let P m (F) be the set of all polynomials with coefficients in F and degree at most m. Then the polynomials 1, z,..., z m span P m (F), so P m (F) is finite dimensional. P(F) is infinite dimensional. F is infinite dimensional. (Tarleton State University) Math 550 Chapter 2 Fall / 20

7 Linear Independence Definition Let v 1,..., v m V. (v 1,..., v m ) is linearly independent if, for any a 1,..., a m F, a 1 v a m v m = 0 implies a 1 = = a m = 0. Otherwise, we say (v 1,..., v m ) is linearly dependent. (v 1,..., v m ) is linearly dependent if there exist a 1,..., a m F such that a 1 v a m v m = 0 and a j 0, for some j {1,..., m}. Any list with 0 is linearly dependent. (v 1 ) is linearly independent iff v 1 0. (v 1, v 2 ) is linearly independent iff neither vector is a scalar multiple of the other. (Tarleton State University) Math 550 Chapter 2 Fall / 20

8 If vectors are removed from a list of linearly independent vectors, the list remains linearly independent. () is linearly independent. (Tarleton State University) Math 550 Chapter 2 Fall / 20

9 Linear Dependence Lemma and a Key Result Lemma Suppose (v 1,..., v m ) is linearly dependent in V, and v 1 0. Then there exists j {2,..., m} such that the following hold: v j span(v 1,..., v j 1 ); if the jth term is removed from (v1,..., v m ), the span of the remaining list equals span(v 1,..., v m ). Theorem Suppose V is finite dimensional, (u 1,..., u m ) is linearly independent in V, and (w 1,..., w n ) spans V. Then m n. That is, linearly independent lists are never longer than spanning lists. (Tarleton State University) Math 550 Chapter 2 Fall / 20

10 Proposition Every subspace of a finite dimensional vector space is finite dimensional. (Tarleton State University) Math 550 Chapter 2 Fall / 20

11 Outline 1 Span and Linear Independence 2 Bases 3 Dimension (Tarleton State University) Math 550 Chapter 2 Fall / 20

12 Bases Definition A list of vectors (v 1,..., v n ) in V is a basis of V if (v 1,..., v n ) is linearly independent, and (v 1,..., v n ) spans V. Example The standard basis (e 1,..., e n ) is a basis of F n. ((1, 2), (3, 5)) is a basis of F 2. ((1, 2)) is not a basis of F 2, since it doesn t span F 2. ((1, 2), (3, 5), (4, 7)) is not a basis of F 2, because it isn t linearly independent. (1, z,..., z m ) is a basis of P m (F). (Tarleton State University) Math 550 Chapter 2 Fall / 20

13 Proposition A list of vectors (v 1,..., v n ) in V is a basis iff every v V can be written uniquely in the form v = a 1 v a n v n, where a 1,..., a n F. (Tarleton State University) Math 550 Chapter 2 Fall / 20

14 Reducing Spanning Lists and Extending Linearly Independent Lists Proposition Every spanning list in V can be reduced to a basis of V. Corollary Every finite-dimensional vector space has a basis. Proposition Every linearly independent list of vectors in a finite dimensional vector space can be extended to a basis of the vector space. (Tarleton State University) Math 550 Chapter 2 Fall / 20

15 Proposition Suppose V is a finite dimensional vector space, and U is a subspace of V. Then there is a subspace W of V such that V = U W. (Tarleton State University) Math 550 Chapter 2 Fall / 20

16 Outline 1 Span and Linear Independence 2 Bases 3 Dimension (Tarleton State University) Math 550 Chapter 2 Fall / 20

17 Dimension Theorem Any two bases of a finite dimensional vector space have the same length. Definition The dimension of a finite dimensional vector space V is the length of any basis of V. dim V denotes the dimension of V. Example dim F n = n. dim P m (F) = m + 1. (Tarleton State University) Math 550 Chapter 2 Fall / 20

18 Proposition If V is finite dimensional, and U is a subspace of V, then dim U dim V. Proposition Suppose dim V = n. Then any spanning list of length n is a basis of V. Also, any linearly independent list of length n is a basis of V. Example ((5, 7), (4, 3)) is a basis for F 2. (Tarleton State University) Math 550 Chapter 2 Fall / 20

19 Two Equations Involving Dimension Theorem If U 1 and U 2 are subspaces of a finite dimensional vector space, then dim(u 1 + U 2 ) = dim U 1 + dim U 2 dim(u 1 U 2 ). Proposition Suppose V is finite dimensional, and V = U U m, where each U j is a subspace of V. Then dim V = dim U dim U m iff V = U 1 U m. Note: this proposition combines Proposition 2.19 and Exercise 17. (Tarleton State University) Math 550 Chapter 2 Fall / 20

20 Hint for Problem 6 on p. 35. For every j = 1, 2,..., define f j (x) = x j. Then show that for any m = 1, 2,..., the functions (f 1,..., f m ) are linearly independent. Hint: use Corollary 4.3 on p. 65. (Tarleton State University) Math 550 Chapter 2 Fall / 20

Math 4153 Exam 1 Review

Math 4153 Exam 1 Review The syllabus for Exam 1 is Chapters 1 3 in Axler. 1. You should be sure to know precise definition of the terms we have used, and you should know precise statements (including all relevant hypotheses)

More information

Problem set #4. Due February 19, x 1 x 2 + x 3 + x 4 x 5 = 0 x 1 + x 3 + 2x 4 = 1 x 1 x 2 x 4 x 5 = 1.

Problem set #4. Due February 19, x 1 x 2 + x 3 + x 4 x 5 = 0 x 1 + x 3 + 2x 4 = 1 x 1 x 2 x 4 x 5 = 1. Problem set #4 Due February 19, 218 The letter V always denotes a vector space. Exercise 1. Find all solutions to 2x 1 x 2 + x 3 + x 4 x 5 = x 1 + x 3 + 2x 4 = 1 x 1 x 2 x 4 x 5 = 1. Solution. First we

More information

1 Invariant subspaces

1 Invariant subspaces MATH 2040 Linear Algebra II Lecture Notes by Martin Li Lecture 8 Eigenvalues, eigenvectors and invariant subspaces 1 In previous lectures we have studied linear maps T : V W from a vector space V to another

More information

Abstract Vector Spaces

Abstract Vector Spaces CHAPTER 1 Abstract Vector Spaces 1.1 Vector Spaces Let K be a field, i.e. a number system where you can add, subtract, multiply and divide. In this course we will take K to be R, C or Q. Definition 1.1.

More information

Chapter 2: Linear Independence and Bases

Chapter 2: Linear Independence and Bases MATH20300: Linear Algebra 2 (2016 Chapter 2: Linear Independence and Bases 1 Linear Combinations and Spans Example 11 Consider the vector v (1, 1 R 2 What is the smallest subspace of (the real vector space

More information

Apprentice Linear Algebra, 1st day, 6/27/05

Apprentice Linear Algebra, 1st day, 6/27/05 Apprentice Linear Algebra, 1st day, 6/7/05 REU 005 Instructor: László Babai Scribe: Eric Patterson Definitions 1.1. An abelian group is a set G with the following properties: (i) ( a, b G)(!a + b G) (ii)

More information

6.4 BASIS AND DIMENSION (Review) DEF 1 Vectors v 1, v 2,, v k in a vector space V are said to form a basis for V if. (a) v 1,, v k span V and

6.4 BASIS AND DIMENSION (Review) DEF 1 Vectors v 1, v 2,, v k in a vector space V are said to form a basis for V if. (a) v 1,, v k span V and 6.4 BASIS AND DIMENSION (Review) DEF 1 Vectors v 1, v 2,, v k in a vector space V are said to form a basis for V if (a) v 1,, v k span V and (b) v 1,, v k are linearly independent. HMHsueh 1 Natural Basis

More information

Lecture 6: Corrections; Dimension; Linear maps

Lecture 6: Corrections; Dimension; Linear maps Lecture 6: Corrections; Dimension; Linear maps Travis Schedler Tues, Sep 28, 2010 (version: Tues, Sep 28, 4:45 PM) Goal To briefly correct the proof of the main Theorem from last time. (See website for

More information

Math 2331 Linear Algebra

Math 2331 Linear Algebra 4.5 The Dimension of a Vector Space Math 233 Linear Algebra 4.5 The Dimension of a Vector Space Shang-Huan Chiu Department of Mathematics, University of Houston schiu@math.uh.edu math.uh.edu/ schiu/ Shang-Huan

More information

Linear Independence. Linear Algebra MATH Linear Algebra LI or LD Chapter 1, Section 7 1 / 1

Linear Independence. Linear Algebra MATH Linear Algebra LI or LD Chapter 1, Section 7 1 / 1 Linear Independence Linear Algebra MATH 76 Linear Algebra LI or LD Chapter, Section 7 / Linear Combinations and Span Suppose s, s,..., s p are scalars and v, v,..., v p are vectors (all in the same space

More information

Footnotes to Linear Algebra (MA 540 fall 2013), T. Goodwillie, Bases

Footnotes to Linear Algebra (MA 540 fall 2013), T. Goodwillie, Bases Footnotes to Linear Algebra (MA 540 fall 2013), T. Goodwillie, Bases November 18, 2013 1 Spanning and linear independence I will outline a slightly different approach to the material in Chapter 2 of Axler

More information

MATH SOLUTIONS TO PRACTICE MIDTERM LECTURE 1, SUMMER Given vector spaces V and W, V W is the vector space given by

MATH SOLUTIONS TO PRACTICE MIDTERM LECTURE 1, SUMMER Given vector spaces V and W, V W is the vector space given by MATH 110 - SOLUTIONS TO PRACTICE MIDTERM LECTURE 1, SUMMER 2009 GSI: SANTIAGO CAÑEZ 1. Given vector spaces V and W, V W is the vector space given by V W = {(v, w) v V and w W }, with addition and scalar

More information

A Do It Yourself Guide to Linear Algebra

A Do It Yourself Guide to Linear Algebra A Do It Yourself Guide to Linear Algebra Lecture Notes based on REUs, 2001-2010 Instructor: László Babai Notes compiled by Howard Liu 6-30-2010 1 Vector Spaces 1.1 Basics Definition 1.1.1. A vector space

More information

Review of Linear Algebra

Review of Linear Algebra Review of Linear Algebra Throughout these notes, F denotes a field (often called the scalars in this context). 1 Definition of a vector space Definition 1.1. A F -vector space or simply a vector space

More information

Math 24 Spring 2012 Questions (mostly) from the Textbook

Math 24 Spring 2012 Questions (mostly) from the Textbook Math 24 Spring 2012 Questions (mostly) from the Textbook 1. TRUE OR FALSE? (a) The zero vector space has no basis. (F) (b) Every vector space that is generated by a finite set has a basis. (c) Every vector

More information

Lecture 9: Vector Algebra

Lecture 9: Vector Algebra Lecture 9: Vector Algebra Linear combination of vectors Geometric interpretation Interpreting as Matrix-Vector Multiplication Span of a set of vectors Vector Spaces and Subspaces Linearly Independent/Dependent

More information

MATH 304 Linear Algebra Lecture 20: The Gram-Schmidt process (continued). Eigenvalues and eigenvectors.

MATH 304 Linear Algebra Lecture 20: The Gram-Schmidt process (continued). Eigenvalues and eigenvectors. MATH 304 Linear Algebra Lecture 20: The Gram-Schmidt process (continued). Eigenvalues and eigenvectors. Orthogonal sets Let V be a vector space with an inner product. Definition. Nonzero vectors v 1,v

More information

Math 54. Selected Solutions for Week 5

Math 54. Selected Solutions for Week 5 Math 54. Selected Solutions for Week 5 Section 4. (Page 94) 8. Consider the following two systems of equations: 5x + x 3x 3 = 5x + x 3x 3 = 9x + x + 5x 3 = 4x + x 6x 3 = 9 9x + x + 5x 3 = 5 4x + x 6x 3

More information

Lecture 4: Linear independence, span, and bases (1)

Lecture 4: Linear independence, span, and bases (1) Lecture 4: Linear independence, span, and bases (1) Travis Schedler Tue, Sep 20, 2011 (version: Wed, Sep 21, 6:30 PM) Goals (2) Understand linear independence and examples Understand span and examples

More information

Vector Spaces and Linear Maps

Vector Spaces and Linear Maps Vector Spaces and Linear Maps Garrett Thomas August 14, 2018 1 About This document is part of a series of notes about math and machine learning. You are free to distribute it as you wish. The latest version

More information

NAME MATH 304 Examination 2 Page 1

NAME MATH 304 Examination 2 Page 1 NAME MATH 4 Examination 2 Page. [8 points (a) Find the following determinant. However, use only properties of determinants, without calculating directly (that is without expanding along a column or row

More information

We showed that adding a vector to a basis produces a linearly dependent set of vectors; more is true.

We showed that adding a vector to a basis produces a linearly dependent set of vectors; more is true. Dimension We showed that adding a vector to a basis produces a linearly dependent set of vectors; more is true. Lemma If a vector space V has a basis B containing n vectors, then any set containing more

More information

19. Basis and Dimension

19. Basis and Dimension 9. Basis and Dimension In the last Section we established the notion of a linearly independent set of vectors in a vector space V and of a set of vectors that span V. We saw that any set of vectors that

More information

LECTURE 6: VECTOR SPACES II (CHAPTER 3 IN THE BOOK)

LECTURE 6: VECTOR SPACES II (CHAPTER 3 IN THE BOOK) LECTURE 6: VECTOR SPACES II (CHAPTER 3 IN THE BOOK) In this lecture, F is a fixed field. One can assume F = R or C. 1. More about the spanning set 1.1. Let S = { v 1, v n } be n vectors in V, we have defined

More information

Linear Independence. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Linear Independence. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Linear Independence MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Introduction Given a set of vectors {v 1, v 2,..., v r } and another vector v span{v 1, v 2,...,

More information

AFFINE AND PROJECTIVE GEOMETRY, E. Rosado & S.L. Rueda 4. BASES AND DIMENSION

AFFINE AND PROJECTIVE GEOMETRY, E. Rosado & S.L. Rueda 4. BASES AND DIMENSION 4. BASES AND DIMENSION Definition Let u 1,..., u n be n vectors in V. The vectors u 1,..., u n are linearly independent if the only linear combination of them equal to the zero vector has only zero scalars;

More information

SUPPLEMENT TO CHAPTER 3

SUPPLEMENT TO CHAPTER 3 SUPPLEMENT TO CHAPTER 3 1.1 Linear combinations and spanning sets Consider the vector space R 3 with the unit vectors e 1 = (1, 0, 0), e 2 = (0, 1, 0), e 3 = (0, 0, 1). Every vector v = (a, b, c) R 3 can

More information

Definition 1. A set V is a vector space over the scalar field F {R, C} iff. there are two operations defined on V, called vector addition

Definition 1. A set V is a vector space over the scalar field F {R, C} iff. there are two operations defined on V, called vector addition 6 Vector Spaces with Inned Product Basis and Dimension Section Objective(s): Vector Spaces and Subspaces Linear (In)dependence Basis and Dimension Inner Product 6 Vector Spaces and Subspaces Definition

More information

Math Linear algebra, Spring Semester Dan Abramovich

Math Linear algebra, Spring Semester Dan Abramovich Math 52 0 - Linear algebra, Spring Semester 2012-2013 Dan Abramovich Fields. We learned to work with fields of numbers in school: Q = fractions of integers R = all real numbers, represented by infinite

More information

Homework 11 Solutions. Math 110, Fall 2013.

Homework 11 Solutions. Math 110, Fall 2013. Homework 11 Solutions Math 110, Fall 2013 1 a) Suppose that T were self-adjoint Then, the Spectral Theorem tells us that there would exist an orthonormal basis of P 2 (R), (p 1, p 2, p 3 ), consisting

More information

Lecture 11: Finish Gaussian elimination and applications; intro to eigenvalues and eigenvectors (1)

Lecture 11: Finish Gaussian elimination and applications; intro to eigenvalues and eigenvectors (1) Lecture 11: Finish Gaussian elimination and applications; intro to eigenvalues and eigenvectors (1) Travis Schedler Tue, Oct 18, 2011 (version: Tue, Oct 18, 6:00 PM) Goals (2) Solving systems of equations

More information

8 General Linear Transformations

8 General Linear Transformations 8 General Linear Transformations 8.1 Basic Properties Definition 8.1 If T : V W is a function from a vector space V into a vector space W, then T is called a linear transformation from V to W if, for all

More information

Row Space, Column Space, and Nullspace

Row Space, Column Space, and Nullspace Row Space, Column Space, and Nullspace MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Introduction Every matrix has associated with it three vector spaces: row space

More information

Worksheet for Lecture 15 (due October 23) Section 4.3 Linearly Independent Sets; Bases

Worksheet for Lecture 15 (due October 23) Section 4.3 Linearly Independent Sets; Bases Worksheet for Lecture 5 (due October 23) Name: Section 4.3 Linearly Independent Sets; Bases Definition An indexed set {v,..., v n } in a vector space V is linearly dependent if there is a linear relation

More information

MATH Linear Algebra

MATH Linear Algebra MATH 304 - Linear Algebra In the previous note we learned an important algorithm to produce orthogonal sequences of vectors called the Gramm-Schmidt orthogonalization process. Gramm-Schmidt orthogonalization

More information

Worksheet for Lecture 25 Section 6.4 Gram-Schmidt Process

Worksheet for Lecture 25 Section 6.4 Gram-Schmidt Process Worksheet for Lecture Name: Section.4 Gram-Schmidt Process Goal For a subspace W = Span{v,..., v n }, we want to find an orthonormal basis of W. Example Let W = Span{x, x } with x = and x =. Give an orthogonal

More information

Dr. Abdulla Eid. Section 4.2 Subspaces. Dr. Abdulla Eid. MATHS 211: Linear Algebra. College of Science

Dr. Abdulla Eid. Section 4.2 Subspaces. Dr. Abdulla Eid. MATHS 211: Linear Algebra. College of Science Section 4.2 Subspaces College of Science MATHS 211: Linear Algebra (University of Bahrain) Subspaces 1 / 42 Goal: 1 Define subspaces. 2 Subspace test. 3 Linear Combination of elements. 4 Subspace generated

More information

Lecture 17: Section 4.2

Lecture 17: Section 4.2 Lecture 17: Section 4.2 Shuanglin Shao November 4, 2013 Subspaces We will discuss subspaces of vector spaces. Subspaces Definition. A subset W is a vector space V is called a subspace of V if W is itself

More information

LECTURES 14/15: LINEAR INDEPENDENCE AND BASES

LECTURES 14/15: LINEAR INDEPENDENCE AND BASES LECTURES 14/15: LINEAR INDEPENDENCE AND BASES MA1111: LINEAR ALGEBRA I, MICHAELMAS 2016 1. Linear Independence We have seen in examples of span sets of vectors that sometimes adding additional vectors

More information

Math 235: Linear Algebra

Math 235: Linear Algebra Math 235: Linear Algebra Midterm Exam 1 October 15, 2013 NAME (please print legibly): Your University ID Number: Please circle your professor s name: Friedmann Tucker The presence of calculators, cell

More information

Solutions to Math 51 Midterm 1 July 6, 2016

Solutions to Math 51 Midterm 1 July 6, 2016 Solutions to Math 5 Midterm July 6, 26. (a) (6 points) Find an equation (of the form ax + by + cz = d) for the plane P in R 3 passing through the points (, 2, ), (2,, ), and (,, ). We first compute two

More information

4 Vector Spaces. 4.1 Basic Definition and Examples. Lecture 10

4 Vector Spaces. 4.1 Basic Definition and Examples. Lecture 10 Lecture 10 4 Vector Spaces 4.1 Basic Definition and Examples Throughout mathematics we come across many types objects which can be added and multiplied by scalars to arrive at similar types of objects.

More information

Linear Algebra. Paul Yiu. Department of Mathematics Florida Atlantic University. Fall 2011

Linear Algebra. Paul Yiu. Department of Mathematics Florida Atlantic University. Fall 2011 Linear Algebra Paul Yiu Department of Mathematics Florida Atlantic University Fall 2011 Linear Algebra Paul Yiu Department of Mathematics Florida Atlantic University Fall 2011 1A: Vector spaces Fields

More information

Linear Algebra Practice Problems

Linear Algebra Practice Problems Linear Algebra Practice Problems Math 24 Calculus III Summer 25, Session II. Determine whether the given set is a vector space. If not, give at least one axiom that is not satisfied. Unless otherwise stated,

More information

Orthonormal Systems. Fourier Series

Orthonormal Systems. Fourier Series Yuliya Gorb Orthonormal Systems. Fourier Series October 31 November 3, 2017 Yuliya Gorb Orthonormal Systems (cont.) Let {e α} α A be an orthonormal set of points in an inner product space X. Then {e α}

More information

Exam 2 Solutions. (a) Is W closed under addition? Why or why not? W is not closed under addition. For example,

Exam 2 Solutions. (a) Is W closed under addition? Why or why not? W is not closed under addition. For example, Exam 2 Solutions. Let V be the set of pairs of real numbers (x, y). Define the following operations on V : (x, y) (x, y ) = (x + x, xx + yy ) r (x, y) = (rx, y) Check if V together with and satisfy properties

More information

LINEAR ALGEBRA BOOT CAMP WEEK 1: THE BASICS

LINEAR ALGEBRA BOOT CAMP WEEK 1: THE BASICS LINEAR ALGEBRA BOOT CAMP WEEK 1: THE BASICS Unless otherwise stated, all vector spaces in this worksheet are finite dimensional and the scalar field F has characteristic zero. The following are facts (in

More information

which are not all zero. The proof in the case where some vector other than combination of the other vectors in S is similar.

which are not all zero. The proof in the case where some vector other than combination of the other vectors in S is similar. It follows that S is linearly dependent since the equation is satisfied by which are not all zero. The proof in the case where some vector other than combination of the other vectors in S is similar. is

More information

2 so Q[ 2] is closed under both additive and multiplicative inverses. a 2 2b 2 + b

2 so Q[ 2] is closed under both additive and multiplicative inverses. a 2 2b 2 + b . FINITE-DIMENSIONAL VECTOR SPACES.. Fields By now you ll have acquired a fair knowledge of matrices. These are a concrete embodiment of something rather more abstract. Sometimes it is easier to use matrices,

More information

1 Last time: inverses

1 Last time: inverses MATH Linear algebra (Fall 8) Lecture 8 Last time: inverses The following all mean the same thing for a function f : X Y : f is invertible f is one-to-one and onto 3 For each b Y there is exactly one a

More information

Chapter 1 Vector Spaces

Chapter 1 Vector Spaces Chapter 1 Vector Spaces Per-Olof Persson persson@berkeley.edu Department of Mathematics University of California, Berkeley Math 110 Linear Algebra Vector Spaces Definition A vector space V over a field

More information

2 Lecture Span, Basis and Dimensions

2 Lecture Span, Basis and Dimensions 2 Lecture 2 2.1 Span, Basis and Dimensions Related to the concept of a linear combination is that of the span. The span of a collection of objects is the set of all linear combinations of those objects

More information

Linear Combination. v = a 1 v 1 + a 2 v a k v k

Linear Combination. v = a 1 v 1 + a 2 v a k v k Linear Combination Definition 1 Given a set of vectors {v 1, v 2,..., v k } in a vector space V, any vector of the form v = a 1 v 1 + a 2 v 2 +... + a k v k for some scalars a 1, a 2,..., a k, is called

More information

Test 3, Linear Algebra

Test 3, Linear Algebra Test 3, Linear Algebra Dr. Adam Graham-Squire, Fall 2017 Name: I pledge that I have neither given nor received any unauthorized assistance on this exam. (signature) DIRECTIONS 1. Don t panic. 2. Show all

More information

Vector Spaces. (1) Every vector space V has a zero vector 0 V

Vector Spaces. (1) Every vector space V has a zero vector 0 V Vector Spaces 1. Vector Spaces A (real) vector space V is a set which has two operations: 1. An association of x, y V to an element x+y V. This operation is called vector addition. 2. The association of

More information

of A in U satisfies S 1 S 2 = { 0}, S 1 + S 2 = R n. Examples 1: (a.) S 1 = span . 1 (c.) S 1 = span, S , S 2 = span 0 (d.

of A in U satisfies S 1 S 2 = { 0}, S 1 + S 2 = R n. Examples 1: (a.) S 1 = span . 1 (c.) S 1 = span, S , S 2 = span 0 (d. . Complements and Projection Maps In this section, we explore the notion of subspaces being complements. Then, the unique decomposition of vectors in R n into two pieces associated to complements lets

More information

BASES. Throughout this note V is a vector space over a scalar field F. N denotes the set of positive integers and i,j,k,l,m,n,p N.

BASES. Throughout this note V is a vector space over a scalar field F. N denotes the set of positive integers and i,j,k,l,m,n,p N. BASES BRANKO ĆURGUS Throughout this note V is a vector space over a scalar field F. N denotes the set of positive integers and i,j,k,l,m,n,p N. 1. Linear independence Definition 1.1. If m N, α 1,...,α

More information

Linear Algebra problems

Linear Algebra problems Linear Algebra problems 1. Show that the set F = ({1, 0}, +,.) is a field where + and. are defined as 1+1=0, 0+0=0, 0+1=1+0=1, 0.0=0.1=1.0=0, 1.1=1.. Let X be a non-empty set and F be any field. Let X

More information

The definition of a vector space (V, +, )

The definition of a vector space (V, +, ) The definition of a vector space (V, +, ) 1. For any u and v in V, u + v is also in V. 2. For any u and v in V, u + v = v + u. 3. For any u, v, w in V, u + ( v + w) = ( u + v) + w. 4. There is an element

More information

Vectors. Vectors and the scalar multiplication and vector addition operations:

Vectors. Vectors and the scalar multiplication and vector addition operations: Vectors Vectors and the scalar multiplication and vector addition operations: x 1 x 1 y 1 2x 1 + 3y 1 x x n 1 = 2 x R n, 2 2 y + 3 2 2x = 2 + 3y 2............ x n x n y n 2x n + 3y n I ll use the two terms

More information

Math 3C Lecture 25. John Douglas Moore

Math 3C Lecture 25. John Douglas Moore Math 3C Lecture 25 John Douglas Moore June 1, 2009 Let V be a vector space. A basis for V is a collection of vectors {v 1,..., v k } such that 1. V = Span{v 1,..., v k }, and 2. {v 1,..., v k } are linearly

More information

Math 24 Winter 2010 Sample Solutions to the Midterm

Math 24 Winter 2010 Sample Solutions to the Midterm Math 4 Winter Sample Solutions to the Midterm (.) (a.) Find a basis {v, v } for the plane P in R with equation x + y z =. We can take any two non-collinear vectors in the plane, for instance v = (,, )

More information

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET This is a (not quite comprehensive) list of definitions and theorems given in Math 1553. Pay particular attention to the ones in red. Study Tip For each

More information

Section 6.2, 6.3 Orthogonal Sets, Orthogonal Projections

Section 6.2, 6.3 Orthogonal Sets, Orthogonal Projections Section 6. 6. Orthogonal Sets Orthogonal Projections Main Ideas in these sections: Orthogonal set = A set of mutually orthogonal vectors. OG LI. Orthogonal Projection of y onto u or onto an OG set {u u

More information

Math 115A: Homework 4

Math 115A: Homework 4 Math A: Homework page question but replace subset by tuple where appropriate and generates with spans page question but replace sets by tuple This won t be graded so do as much as you need Find bases for

More information

Math Linear Algebra

Math Linear Algebra Math 220 - Linear Algebra (Summer 208) Solutions to Homework #7 Exercise 6..20 (a) TRUE. u v v u = 0 is equivalent to u v = v u. The latter identity is true due to the commutative property of the inner

More information

MATH 1120 (LINEAR ALGEBRA 1), FINAL EXAM FALL 2011 SOLUTIONS TO PRACTICE VERSION

MATH 1120 (LINEAR ALGEBRA 1), FINAL EXAM FALL 2011 SOLUTIONS TO PRACTICE VERSION MATH (LINEAR ALGEBRA ) FINAL EXAM FALL SOLUTIONS TO PRACTICE VERSION Problem (a) For each matrix below (i) find a basis for its column space (ii) find a basis for its row space (iii) determine whether

More information

Math 4A Notes. Written by Victoria Kala Last updated June 11, 2017

Math 4A Notes. Written by Victoria Kala Last updated June 11, 2017 Math 4A Notes Written by Victoria Kala vtkala@math.ucsb.edu Last updated June 11, 2017 Systems of Linear Equations A linear equation is an equation that can be written in the form a 1 x 1 + a 2 x 2 +...

More information

MATH 304 Linear Algebra Lecture 10: Linear independence. Wronskian.

MATH 304 Linear Algebra Lecture 10: Linear independence. Wronskian. MATH 304 Linear Algebra Lecture 10: Linear independence. Wronskian. Spanning set Let S be a subset of a vector space V. Definition. The span of the set S is the smallest subspace W V that contains S. If

More information

Chapter 2. General Vector Spaces. 2.1 Real Vector Spaces

Chapter 2. General Vector Spaces. 2.1 Real Vector Spaces Chapter 2 General Vector Spaces Outline : Real vector spaces Subspaces Linear independence Basis and dimension Row Space, Column Space, and Nullspace 2 Real Vector Spaces 2 Example () Let u and v be vectors

More information

Linear Algebra 2 Spectral Notes

Linear Algebra 2 Spectral Notes Linear Algebra 2 Spectral Notes In what follows, V is an inner product vector space over F, where F = R or C. We will use results seen so far; in particular that every linear operator T L(V ) has a complex

More information

A linear algebra proof of the fundamental theorem of algebra

A linear algebra proof of the fundamental theorem of algebra A linear algebra proof of the fundamental theorem of algebra Andrés E. Caicedo May 18, 2010 Abstract We present a recent proof due to Harm Derksen, that any linear operator in a complex finite dimensional

More information

A linear algebra proof of the fundamental theorem of algebra

A linear algebra proof of the fundamental theorem of algebra A linear algebra proof of the fundamental theorem of algebra Andrés E. Caicedo May 18, 2010 Abstract We present a recent proof due to Harm Derksen, that any linear operator in a complex finite dimensional

More information

Chapter 3. More about Vector Spaces Linear Independence, Basis and Dimension. Contents. 1 Linear Combinations, Span

Chapter 3. More about Vector Spaces Linear Independence, Basis and Dimension. Contents. 1 Linear Combinations, Span Chapter 3 More about Vector Spaces Linear Independence, Basis and Dimension Vincent Astier, School of Mathematical Sciences, University College Dublin 3. Contents Linear Combinations, Span Linear Independence,

More information

MATH 115A: SAMPLE FINAL SOLUTIONS

MATH 115A: SAMPLE FINAL SOLUTIONS MATH A: SAMPLE FINAL SOLUTIONS JOE HUGHES. Let V be the set of all functions f : R R such that f( x) = f(x) for all x R. Show that V is a vector space over R under the usual addition and scalar multiplication

More information

Vector Spaces and SubSpaces

Vector Spaces and SubSpaces Vector Spaces and SubSpaces Linear Algebra MATH 2076 Linear Algebra Vector Spaces & SubSpaces Chapter 4, Section 1b 1 / 10 What is a Vector Space? A vector space is a bunch of objects that we call vectors

More information

MATH 323 Linear Algebra Lecture 12: Basis of a vector space (continued). Rank and nullity of a matrix.

MATH 323 Linear Algebra Lecture 12: Basis of a vector space (continued). Rank and nullity of a matrix. MATH 323 Linear Algebra Lecture 12: Basis of a vector space (continued). Rank and nullity of a matrix. Basis Definition. Let V be a vector space. A linearly independent spanning set for V is called a basis.

More information

Worksheet for Lecture 15 (due October 23) Section 4.3 Linearly Independent Sets; Bases

Worksheet for Lecture 15 (due October 23) Section 4.3 Linearly Independent Sets; Bases Worksheet for Lecture 5 (due October 23) Name: Section 4.3 Linearly Independent Sets; Bases Definition An indexed set {v,..., v n } in a vector space V is linearly dependent if there is a linear relation

More information

Orthonormal Bases; Gram-Schmidt Process; QR-Decomposition

Orthonormal Bases; Gram-Schmidt Process; QR-Decomposition Orthonormal Bases; Gram-Schmidt Process; QR-Decomposition MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 205 Motivation When working with an inner product space, the most

More information

Math 3191 Applied Linear Algebra

Math 3191 Applied Linear Algebra Math 9 Applied Linear Algebra Lecture : Null and Column Spaces Stephen Billups University of Colorado at Denver Math 9Applied Linear Algebra p./8 Announcements Study Guide posted HWK posted Math 9Applied

More information

Advanced Engineering Mathematics Prof. Pratima Panigrahi Department of Mathematics Indian Institute of Technology, Kharagpur

Advanced Engineering Mathematics Prof. Pratima Panigrahi Department of Mathematics Indian Institute of Technology, Kharagpur Advanced Engineering Mathematics Prof. Pratima Panigrahi Department of Mathematics Indian Institute of Technology, Kharagpur Lecture No. # 02 Vector Spaces, Subspaces, linearly Dependent/Independent of

More information

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET

IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET IMPORTANT DEFINITIONS AND THEOREMS REFERENCE SHEET This is a (not quite comprehensive) list of definitions and theorems given in Math 1553. Pay particular attention to the ones in red. Study Tip For each

More information

MTH5102 Spring 2017 HW Assignment 3: Sec. 1.5, #2(e), 9, 15, 20; Sec. 1.6, #7, 13, 29 The due date for this assignment is 2/01/17.

MTH5102 Spring 2017 HW Assignment 3: Sec. 1.5, #2(e), 9, 15, 20; Sec. 1.6, #7, 13, 29 The due date for this assignment is 2/01/17. MTH5102 Spring 2017 HW Assignment 3: Sec. 1.5, #2(e), 9, 15, 20; Sec. 1.6, #7, 13, 29 The due date for this assignment is 2/01/17. Sec. 1.5, #2(e). Determine whether the following sets are linearly dependent

More information

Solutions to Homework 5 - Math 3410

Solutions to Homework 5 - Math 3410 Solutions to Homework 5 - Math 34 (Page 57: # 489) Determine whether the following vectors in R 4 are linearly dependent or independent: (a) (, 2, 3, ), (3, 7,, 2), (, 3, 7, 4) Solution From x(, 2, 3,

More information

MATH 225 Summer 2005 Linear Algebra II Solutions to Assignment 1 Due: Wednesday July 13, 2005

MATH 225 Summer 2005 Linear Algebra II Solutions to Assignment 1 Due: Wednesday July 13, 2005 MATH 225 Summer 25 Linear Algebra II Solutions to Assignment 1 Due: Wednesday July 13, 25 Department of Mathematical and Statistical Sciences University of Alberta Question 1. [p 224. #2] The set of all

More information

Linear Algebra. Chapter 5

Linear Algebra. Chapter 5 Chapter 5 Linear Algebra The guiding theme in linear algebra is the interplay between algebraic manipulations and geometric interpretations. This dual representation is what makes linear algebra a fruitful

More information

Math 2331 Linear Algebra

Math 2331 Linear Algebra 4.3 Linearly Independent Sets; Bases Math 233 Linear Algebra 4.3 Linearly Independent Sets; Bases Jiwen He Department of Mathematics, University of Houston jiwenhe@math.uh.edu math.uh.edu/ jiwenhe/math233

More information

Math 4377/6308 Advanced Linear Algebra I Dr. Vaughn Climenhaga, PGH 651A HOMEWORK 3

Math 4377/6308 Advanced Linear Algebra I Dr. Vaughn Climenhaga, PGH 651A HOMEWORK 3 Math 4377/6308 Advanced Linear Algebra I Dr. Vaughn Climenhaga, PGH 651A Fall 2013 HOMEWORK 3 Due 4pm Wednesday, September 11. You will be graded not only on the correctness of your answers but also on

More information

Fall 2016 MATH*1160 Final Exam

Fall 2016 MATH*1160 Final Exam Fall 2016 MATH*1160 Final Exam Last name: (PRINT) First name: Student #: Instructor: M. R. Garvie Dec 16, 2016 INSTRUCTIONS: 1. The exam is 2 hours long. Do NOT start until instructed. You may use blank

More information

MATH 221: SOLUTIONS TO SELECTED HOMEWORK PROBLEMS

MATH 221: SOLUTIONS TO SELECTED HOMEWORK PROBLEMS MATH 221: SOLUTIONS TO SELECTED HOMEWORK PROBLEMS 1. HW 1: Due September 4 1.1.21. Suppose v, w R n and c is a scalar. Prove that Span(v + cw, w) = Span(v, w). We must prove two things: that every element

More information

Second Exam. Math , Spring March 2015

Second Exam. Math , Spring March 2015 Second Exam Math 34-54, Spring 25 3 March 25. This exam has 8 questions and 2 pages. Make sure you have all pages before you begin. The eighth question is bonus (and worth less than the others). 2. This

More information

Math Linear Algebra Final Exam Review Sheet

Math Linear Algebra Final Exam Review Sheet Math 15-1 Linear Algebra Final Exam Review Sheet Vector Operations Vector addition is a component-wise operation. Two vectors v and w may be added together as long as they contain the same number n of

More information

Lecture 11. Andrei Antonenko. February 26, Last time we studied bases of vector spaces. Today we re going to give some examples of bases.

Lecture 11. Andrei Antonenko. February 26, Last time we studied bases of vector spaces. Today we re going to give some examples of bases. Lecture 11 Andrei Antonenko February 6, 003 1 Examples of bases Last time we studied bases of vector spaces. Today we re going to give some examples of bases. Example 1.1. Consider the vector space P the

More information

Math 121 Homework 4: Notes on Selected Problems

Math 121 Homework 4: Notes on Selected Problems Math 121 Homework 4: Notes on Selected Problems 11.2.9. If W is a subspace of the vector space V stable under the linear transformation (i.e., (W ) W ), show that induces linear transformations W on W

More information

Advanced Linear Algebra Math 4377 / 6308 (Spring 2015) March 5, 2015

Advanced Linear Algebra Math 4377 / 6308 (Spring 2015) March 5, 2015 Midterm 1 Advanced Linear Algebra Math 4377 / 638 (Spring 215) March 5, 215 2 points 1. Mark each statement True or False. Justify each answer. (If true, cite appropriate facts or theorems. If false, explain

More information

Linear Independence. Consider a plane P that includes the origin in R 3 {u, v, w} in P. and non-zero vectors

Linear Independence. Consider a plane P that includes the origin in R 3 {u, v, w} in P. and non-zero vectors Linear Independence Consider a plane P that includes the origin in R 3 {u, v, w} in P. and non-zero vectors If no two of u, v and w are parallel, then P =span{u, v, w}. But any two vectors determines a

More information

Linear Algebra, Spring 2005

Linear Algebra, Spring 2005 Linear Algebra, Spring 2005 Solutions May 4, 2005 Problem 4.89 To check for linear independence write the vectors as rows of a matrix. Reduce the matrix to echelon form and determine the number of non-zero

More information

Let V be a vector space, and let X be a subset. We say X is a Basis if it is both linearly independent and a generating set.

Let V be a vector space, and let X be a subset. We say X is a Basis if it is both linearly independent and a generating set. Basis Let V be a vector space, and let X be a subset. We say X is a Basis if it is both linearly independent and a generating set. The first example of a basis is the standard basis for R n e 1 = (1, 0,...,

More information

August 23, 2017 Let us measure everything that is measurable, and make measurable everything that is not yet so. Galileo Galilei. 1.

August 23, 2017 Let us measure everything that is measurable, and make measurable everything that is not yet so. Galileo Galilei. 1. August 23, 2017 Let us measure everything that is measurable, and make measurable everything that is not yet so. Galileo Galilei 1. Vector spaces 1.1. Notations. x S denotes the fact that the element x

More information

0.2 Vector spaces. J.A.Beachy 1

0.2 Vector spaces. J.A.Beachy 1 J.A.Beachy 1 0.2 Vector spaces I m going to begin this section at a rather basic level, giving the definitions of a field and of a vector space in much that same detail as you would have met them in a

More information