Solutions to Section 2.9 Homework Problems Problems 1 5, 7, 9, 10 15, (odd), and 38. S. F. Ellermeyer June 21, 2002

Size: px
Start display at page:

Download "Solutions to Section 2.9 Homework Problems Problems 1 5, 7, 9, 10 15, (odd), and 38. S. F. Ellermeyer June 21, 2002"

Transcription

1 Solutions to Section 9 Homework Problems Problems 9 (odd) and 8 S F Ellermeyer June The pictured set contains the vector u but not the vector u so this set is not a subspace of The pictured set contains the vectors u and v but not the vector u v so this set is not a subspace of The picture set contains some short vectors in the second quadrant but not all scalar multiples of these vectors so this set is not a subspace of The pictured set contains the vector u u so this set is not a subspace of but not the vector To determine if w is in the subspace generated by v and v we must determine if w can be written as a linear combination of v and v The equivalence shows that w is not in the subspace generated by v and v (because the equation v v x w is inconsistent) a There are three vectors in the set v v v b There are infinitely many vectors in ColA c The equivalence shows that p is in ColA In particular we see that p 9 v v (and there are infinitely many other ways to write p as a linear

2 combination of v v and v ) 9 NulA consists of all solutions of the equation Ax Note that 6 Ap so p is not in NulA Au 6 6 so u is in NulA NulA is a subspace of and ColA is a subspace of NulA is a subspace of and ColA is a subspace of Using the equivalence 9 9 we see that a non zero vector in NulA is x (This was obtained by setting both free variables x and x equal to ) Obtaining a non zero vector in ColA is easy: We just take a linear combination of the columns of A such as a a a a Using the equivalence

3 we see that a non zero vector in NulA is x A non zero vector in ColA is a a a This is a set of two linearly independent vectors in and hence is a basis for Since 6 these vectors form a basis for 9 Since has dimension every basis for must contain exactly three vectors Thus the given vectors do not form a basis for (since there are only two vectors in the given set) Since columns and are the pivot columns of A a basis for ColA is a a where Also since a A and a 8 we see that the general solution of Ax is x x x and since the vectors that appear on the right hand side of the above 8

4 equation are linearly independent a basis for NulA is v v where v and v Since columns and are the pivot columns of A a basis for ColA is a a a where 8 a a and a 6 Also since 9 A we see that the general solution of Ax is x x x and since the vectors that appear on the right hand side of the above equation are linearly independent a basis for NulA is v v where v and v The subspace of spanned by the given set of vectors is the column space of the matrix 9 9

5 Since A A 8 we see that the pivot columns of A are columns and Thus a basis for the subspace spanned by the given vectors is a a a where a a a If A is a x matrix with three pivot columns then the vectors in these three columns are a basis for ColA Thus ColA is three dimensional and is a subset of This means that ColA Since the equation Ax has two free variables NulA is two dimensional However note that NulA is a subset of Thus NulA is a two dimensional subspace of In this case we should not say that NulA but rather that NulA a subspace of that is isomorphic to We picture NulA as a plane in passing through the origin in (although it is impossible for us to actually visualize a five dimensional space) 9 The coordinate vector of x relative to the basis B is the solution of the equation Ax b which shows that x B Note that the subspace in this problem is a two dimensional subspace of (a plane passing through the origin in ) Also

6 so x B If the null space of a x matrix is four dimensional then the column space of this matrix is three-dimensional (This is by the Rank Theorem) If A is a x6 matrix and the solution space of Ax has a basis consisting of two vectors then NulA is two dimensional which means that ColA is four dimensional (by the Rank Theorem) Thus RankA a False (or really just stated in a way that does not make sense) A subspace of n is a subset H of n such that i The zero vector is in H ii If u and v are any two vectors in H then the vector u v is in H iii If u is any vector in H and c is any scalar then the vector cu is in H b True c False It is a subspace of m d False The pivot columns of A form a basis for ColA e True 8 a False See the answer to problem a where a correct definition of the term subspace is given b False The column space of A is the space spanned by the columns of A c True d True e True 6

2018 Fall 2210Q Section 013 Midterm Exam II Solution

2018 Fall 2210Q Section 013 Midterm Exam II Solution 08 Fall 0Q Section 0 Midterm Exam II Solution True or False questions points 0 0 points) ) Let A be an n n matrix. If the equation Ax b has at least one solution for each b R n, then the solution is unique

More information

Review Notes for Linear Algebra True or False Last Updated: February 22, 2010

Review Notes for Linear Algebra True or False Last Updated: February 22, 2010 Review Notes for Linear Algebra True or False Last Updated: February 22, 2010 Chapter 4 [ Vector Spaces 4.1 If {v 1,v 2,,v n } and {w 1,w 2,,w n } are linearly independent, then {v 1 +w 1,v 2 +w 2,,v n

More information

Math 102, Winter 2009, Homework 7

Math 102, Winter 2009, Homework 7 Math 2, Winter 29, Homework 7 () Find the standard matrix of the linear transformation T : R 3 R 3 obtained by reflection through the plane x + z = followed by a rotation about the positive x-axes by 6

More information

What is on this week. 1 Vector spaces (continued) 1.1 Null space and Column Space of a matrix

What is on this week. 1 Vector spaces (continued) 1.1 Null space and Column Space of a matrix Professor Joana Amorim, jamorim@bu.edu What is on this week Vector spaces (continued). Null space and Column Space of a matrix............................. Null Space...........................................2

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

Vector space and subspace

Vector space and subspace Vector space and subspace Math 112, week 8 Goals: Vector space, subspace, span. Null space, column space. Linearly independent, bases. Suggested Textbook Readings: Sections 4.1, 4.2, 4.3 Week 8: Vector

More information

Sept. 26, 2013 Math 3312 sec 003 Fall 2013

Sept. 26, 2013 Math 3312 sec 003 Fall 2013 Sept. 26, 2013 Math 3312 sec 003 Fall 2013 Section 4.1: Vector Spaces and Subspaces Definition A vector space is a nonempty set V of objects called vectors together with two operations called vector addition

More information

Final Examination 201-NYC-05 December and b =

Final Examination 201-NYC-05 December and b = . (5 points) Given A [ 6 5 8 [ and b (a) Express the general solution of Ax b in parametric vector form. (b) Given that is a particular solution to Ax d, express the general solution to Ax d in parametric

More information

MATH 2210Q MIDTERM EXAM I PRACTICE PROBLEMS

MATH 2210Q MIDTERM EXAM I PRACTICE PROBLEMS MATH Q MIDTERM EXAM I PRACTICE PROBLEMS Date and place: Thursday, November, 8, in-class exam Section : : :5pm at MONT Section : 9: :5pm at MONT 5 Material: Sections,, 7 Lecture 9 8, Quiz, Worksheet 9 8,

More information

Worksheet for Lecture 23 (due December 4) Section 6.1 Inner product, length, and orthogonality

Worksheet for Lecture 23 (due December 4) Section 6.1 Inner product, length, and orthogonality Worksheet for Lecture (due December 4) Name: Section 6 Inner product, length, and orthogonality u Definition Let u = u n product or dot product to be and v = v v n be vectors in R n We define their inner

More information

1. Determine by inspection which of the following sets of vectors is linearly independent. 3 3.

1. Determine by inspection which of the following sets of vectors is linearly independent. 3 3. 1. Determine by inspection which of the following sets of vectors is linearly independent. (a) (d) 1, 3 4, 1 { [ [,, 1 1] 3]} (b) 1, 4 5, (c) 3 6 (e) 1, 3, 4 4 3 1 4 Solution. The answer is (a): v 1 is

More information

MATH 2331 Linear Algebra. Section 2.1 Matrix Operations. Definition: A : m n, B : n p. Example: Compute AB, if possible.

MATH 2331 Linear Algebra. Section 2.1 Matrix Operations. Definition: A : m n, B : n p. Example: Compute AB, if possible. MATH 2331 Linear Algebra Section 2.1 Matrix Operations Definition: A : m n, B : n p ( 1 2 p ) ( 1 2 p ) AB = A b b b = Ab Ab Ab Example: Compute AB, if possible. 1 Row-column rule: i-j-th entry of AB:

More information

ft-uiowa-math2550 Assignment OptionalFinalExamReviewMultChoiceMEDIUMlengthForm due 12/31/2014 at 10:36pm CST

ft-uiowa-math2550 Assignment OptionalFinalExamReviewMultChoiceMEDIUMlengthForm due 12/31/2014 at 10:36pm CST me me ft-uiowa-math255 Assignment OptionalFinalExamReviewMultChoiceMEDIUMlengthForm due 2/3/2 at :3pm CST. ( pt) Library/TCNJ/TCNJ LinearSystems/problem3.pg Give a geometric description of the following

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

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

Practice Final Exam. Solutions.

Practice Final Exam. Solutions. MATH Applied Linear Algebra December 6, 8 Practice Final Exam Solutions Find the standard matrix f the linear transfmation T : R R such that T, T, T Solution: Easy to see that the transfmation T can be

More information

DEPARTMENT OF MATHEMATICS

DEPARTMENT OF MATHEMATICS DEPARTMENT OF MATHEMATICS. Points: 4+7+4 Ma 322 Solved First Exam February 7, 207 With supplements You are given an augmented matrix of a linear system of equations. Here t is a parameter: 0 4 4 t 0 3

More information

Chapter 3. Directions: For questions 1-11 mark each statement True or False. Justify each answer.

Chapter 3. Directions: For questions 1-11 mark each statement True or False. Justify each answer. Chapter 3 Directions: For questions 1-11 mark each statement True or False. Justify each answer. 1. (True False) Asking whether the linear system corresponding to an augmented matrix [ a 1 a 2 a 3 b ]

More information

Solutions to Math 51 First Exam April 21, 2011

Solutions to Math 51 First Exam April 21, 2011 Solutions to Math 5 First Exam April,. ( points) (a) Give the precise definition of a (linear) subspace V of R n. (4 points) A linear subspace V of R n is a subset V R n which satisfies V. If x, y V then

More information

Kevin James. MTHSC 3110 Section 4.3 Linear Independence in Vector Sp

Kevin James. MTHSC 3110 Section 4.3 Linear Independence in Vector Sp MTHSC 3 Section 4.3 Linear Independence in Vector Spaces; Bases Definition Let V be a vector space and let { v. v 2,..., v p } V. If the only solution to the equation x v + x 2 v 2 + + x p v p = is the

More information

1. Let A = (a) 2 (b) 3 (c) 0 (d) 4 (e) 1

1. Let A = (a) 2 (b) 3 (c) 0 (d) 4 (e) 1 . Let A =. The rank of A is (a) (b) (c) (d) (e). Let P = {a +a t+a t } where {a,a,a } range over all real numbers, and let T : P P be a linear transformation dedifined by T (a + a t + a t )=a +9a t If

More information

Midterm #2 Solutions

Midterm #2 Solutions Naneh Apkarian Math F Winter Midterm # Solutions Here is a solution key for the second midterm. The solutions presented here are more complete and thorough than your responses needed to be - in order to

More information

DIAGONALIZATION. In order to see the implications of this definition, let us consider the following example Example 1. Consider the matrix

DIAGONALIZATION. In order to see the implications of this definition, let us consider the following example Example 1. Consider the matrix DIAGONALIZATION Definition We say that a matrix A of size n n is diagonalizable if there is a basis of R n consisting of eigenvectors of A ie if there are n linearly independent vectors v v n such that

More information

PRACTICE PROBLEMS FOR THE FINAL

PRACTICE PROBLEMS FOR THE FINAL PRACTICE PROBLEMS FOR THE FINAL Here are a slew of practice problems for the final culled from old exams:. Let P be the vector space of polynomials of degree at most. Let B = {, (t ), t + t }. (a) Show

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

Review for Chapter 1. Selected Topics

Review for Chapter 1. Selected Topics Review for Chapter 1 Selected Topics Linear Equations We have four equivalent ways of writing linear systems: 1 As a system of equations: 2x 1 + 3x 2 = 7 x 1 x 2 = 5 2 As an augmented matrix: ( 2 3 ) 7

More information

Review Notes for Midterm #2

Review Notes for Midterm #2 Review Notes for Midterm #2 Joris Vankerschaver This version: Nov. 2, 200 Abstract This is a summary of the basic definitions and results that we discussed during class. Whenever a proof is provided, I

More information

R b. x 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 x 9 1 1, x h. , x p. x 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 x 9

R b. x 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 x 9 1 1, x h. , x p. x 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 x 9 The full solution of Ax b x x p x h : The general solution is the sum of any particular solution of the system Ax b plus the general solution of the corresponding homogeneous system Ax. ) Reduce A b to

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

(a) only (ii) and (iv) (b) only (ii) and (iii) (c) only (i) and (ii) (d) only (iv) (e) only (i) and (iii)

(a) only (ii) and (iv) (b) only (ii) and (iii) (c) only (i) and (ii) (d) only (iv) (e) only (i) and (iii) . Which of the following are Vector Spaces? (i) V = { polynomials of the form q(t) = t 3 + at 2 + bt + c : a b c are real numbers} (ii) V = {at { 2 + b : a b are real numbers} } a (iii) V = : a 0 b is

More information

Objective: Introduction of vector spaces, subspaces, and bases. Linear Algebra: Section

Objective: Introduction of vector spaces, subspaces, and bases. Linear Algebra: Section Objective: Introduction of vector spaces, subspaces, and bases. Vector space Vector space Examples: R n, subsets of R n, the set of polynomials (up to degree n), the set of (continuous, differentiable)

More information

ICS 6N Computational Linear Algebra Vector Space

ICS 6N Computational Linear Algebra Vector Space ICS 6N Computational Linear Algebra Vector Space Xiaohui Xie University of California, Irvine xhx@uci.edu Xiaohui Xie (UCI) ICS 6N 1 / 24 Vector Space Definition: A vector space is a non empty set V of

More information

Math 369 Exam #2 Practice Problem Solutions

Math 369 Exam #2 Practice Problem Solutions Math 369 Exam #2 Practice Problem Solutions 2 5. Is { 2, 3, 8 } a basis for R 3? Answer: No, it is not. To show that it is not a basis, it suffices to show that this is not a linearly independent set.

More information

1 Systems of equations

1 Systems of equations Highlights from linear algebra David Milovich, Math 2 TA for sections -6 November, 28 Systems of equations A leading entry in a matrix is the first (leftmost) nonzero entry of a row. For example, the leading

More information

Linear independence, span, basis, dimension - and their connection with linear systems

Linear independence, span, basis, dimension - and their connection with linear systems Linear independence span basis dimension - and their connection with linear systems Linear independence of a set of vectors: We say the set of vectors v v..v k is linearly independent provided c v c v..c

More information

2. (10 pts) How many vectors are in the null space of the matrix A = 0 1 1? (i). Zero. (iv). Three. (ii). One. (v).

2. (10 pts) How many vectors are in the null space of the matrix A = 0 1 1? (i). Zero. (iv). Three. (ii). One. (v). Exam 3 MAS 3105 Applied Linear Algebra, Spring 2018 (Clearly!) Print Name: Apr 10, 2018 Read all of what follows carefully before starting! 1. This test has 7 problems and is worth 110 points. Please be

More information

GENERAL VECTOR SPACES AND SUBSPACES [4.1]

GENERAL VECTOR SPACES AND SUBSPACES [4.1] GENERAL VECTOR SPACES AND SUBSPACES [4.1] General vector spaces So far we have seen special spaces of vectors of n dimensions denoted by R n. It is possible to define more general vector spaces A vector

More information

Lecture 22: Section 4.7

Lecture 22: Section 4.7 Lecture 22: Section 47 Shuanglin Shao December 2, 213 Row Space, Column Space, and Null Space Definition For an m n, a 11 a 12 a 1n a 21 a 22 a 2n A = a m1 a m2 a mn, the vectors r 1 = [ a 11 a 12 a 1n

More information

Lecture 13: Row and column spaces

Lecture 13: Row and column spaces Spring 2018 UW-Madison Lecture 13: Row and column spaces 1 The column space of a matrix 1.1 Definition The column space of matrix A denoted as Col(A) is the space consisting of all linear combinations

More information

MATH SOLUTIONS TO PRACTICE PROBLEMS - MIDTERM I. 1. We carry out row reduction. We begin with the row operations

MATH SOLUTIONS TO PRACTICE PROBLEMS - MIDTERM I. 1. We carry out row reduction. We begin with the row operations MATH 2 - SOLUTIONS TO PRACTICE PROBLEMS - MIDTERM I. We carry out row reduction. We begin with the row operations yielding the matrix This is already upper triangular hence The lower triangular matrix

More information

Math 54 HW 4 solutions

Math 54 HW 4 solutions Math 54 HW 4 solutions 2.2. Section 2.2 (a) False: Recall that performing a series of elementary row operations A is equivalent to multiplying A by a series of elementary matrices. Suppose that E,...,

More information

Math 54 First Midterm Exam, Prof. Srivastava September 23, 2016, 4:10pm 5:00pm, 155 Dwinelle Hall.

Math 54 First Midterm Exam, Prof. Srivastava September 23, 2016, 4:10pm 5:00pm, 155 Dwinelle Hall. Math 54 First Midterm Exam, Prof Srivastava September 23, 26, 4:pm 5:pm, 55 Dwinelle Hall Name: SID: Instructions: Write all answers in the provided space This exam includes two pages of scratch paper,

More information

YORK UNIVERSITY. Faculty of Science Department of Mathematics and Statistics MATH M Test #1. July 11, 2013 Solutions

YORK UNIVERSITY. Faculty of Science Department of Mathematics and Statistics MATH M Test #1. July 11, 2013 Solutions YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH 222 3. M Test # July, 23 Solutions. For each statement indicate whether it is always TRUE or sometimes FALSE. Note: For

More information

Math 4377/6308 Advanced Linear Algebra

Math 4377/6308 Advanced Linear Algebra 2. Linear Transformations Math 4377/638 Advanced Linear Algebra 2. Linear Transformations, Null Spaces and Ranges Jiwen He Department of Mathematics, University of Houston jiwenhe@math.uh.edu math.uh.edu/

More information

EK102 Linear Algebra PRACTICE PROBLEMS for Final Exam Spring 2016

EK102 Linear Algebra PRACTICE PROBLEMS for Final Exam Spring 2016 EK102 Linear Algebra PRACTICE PROBLEMS for Final Exam Spring 2016 Answer the questions in the spaces provided on the question sheets. You must show your work to get credit for your answers. There will

More information

Study Guide for Linear Algebra Exam 2

Study Guide for Linear Algebra Exam 2 Study Guide for Linear Algebra Exam 2 Term Vector Space Definition A Vector Space is a nonempty set V of objects, on which are defined two operations, called addition and multiplication by scalars (real

More information

Homework Set #8 Solutions

Homework Set #8 Solutions Exercises.2 (p. 19) Homework Set #8 Solutions Assignment: Do #6, 8, 12, 14, 2, 24, 26, 29, 0, 2, 4, 5, 6, 9, 40, 42 6. Reducing the matrix to echelon form: 1 5 2 1 R2 R2 R1 1 5 0 18 12 2 1 R R 2R1 1 5

More information

(v, w) = arccos( < v, w >

(v, w) = arccos( < v, w > MA322 F all206 Notes on Inner Products Notes on Chapter 6 Inner product. Given a real vector space V, an inner product is defined to be a bilinear map F : V V R such that the following holds: Commutativity:

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

χ 1 χ 2 and ψ 1 ψ 2 is also in the plane: αχ 1 αχ 2 which has a zero first component and hence is in the plane. is also in the plane: ψ 1

χ 1 χ 2 and ψ 1 ψ 2 is also in the plane: αχ 1 αχ 2 which has a zero first component and hence is in the plane. is also in the plane: ψ 1 58 Chapter 5 Vector Spaces: Theory and Practice 57 s Which of the following subsets of R 3 are actually subspaces? (a The plane of vectors x =(χ,χ, T R 3 such that the first component χ = In other words,

More information

Math 22 Fall 2018 Midterm 2

Math 22 Fall 2018 Midterm 2 Math 22 Fall 218 Midterm 2 October 23, 218 NAME: SECTION (check one box): Section 1 (S. Allen 12:5) Section 2 (A. Babei 2:1) Instructions: 1. Write your name legibly on this page, and indicate your section

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

(a) II and III (b) I (c) I and III (d) I and II and III (e) None are true.

(a) II and III (b) I (c) I and III (d) I and II and III (e) None are true. 1 Which of the following statements is always true? I The null space of an m n matrix is a subspace of R m II If the set B = {v 1,, v n } spans a vector space V and dimv = n, then B is a basis for V III

More information

Homework 5. (due Wednesday 8 th Nov midnight)

Homework 5. (due Wednesday 8 th Nov midnight) Homework (due Wednesday 8 th Nov midnight) Use this definition for Column Space of a Matrix Column Space of a matrix A is the set ColA of all linear combinations of the columns of A. In other words, if

More information

Math 1553 Introduction to Linear Algebra

Math 1553 Introduction to Linear Algebra Math 1553 Introduction to Linear Algebra Lecture Notes Chapter 2 Matrix Algebra School of Mathematics The Georgia Institute of Technology Math 1553 Lecture Notes for Chapter 2 Introduction, Slide 1 Section

More information

Final Examination 201-NYC-05 - Linear Algebra I December 8 th, and b = 4. Find the value(s) of a for which the equation Ax = b

Final Examination 201-NYC-05 - Linear Algebra I December 8 th, and b = 4. Find the value(s) of a for which the equation Ax = b Final Examination -NYC-5 - Linear Algebra I December 8 th 7. (4 points) Let A = has: (a) a unique solution. a a (b) infinitely many solutions. (c) no solution. and b = 4. Find the value(s) of a for which

More information

MATH 2331 Linear Algebra. Section 1.1 Systems of Linear Equations. Finding the solution to a set of two equations in two variables: Example 1: Solve:

MATH 2331 Linear Algebra. Section 1.1 Systems of Linear Equations. Finding the solution to a set of two equations in two variables: Example 1: Solve: MATH 2331 Linear Algebra Section 1.1 Systems of Linear Equations Finding the solution to a set of two equations in two variables: Example 1: Solve: x x = 3 1 2 2x + 4x = 12 1 2 Geometric meaning: Do these

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

Math 21b: Linear Algebra Spring 2018

Math 21b: Linear Algebra Spring 2018 Math b: Linear Algebra Spring 08 Homework 8: Basis This homework is due on Wednesday, February 4, respectively on Thursday, February 5, 08. Which of the following sets are linear spaces? Check in each

More information

Math 314H EXAM I. 1. (28 points) The row reduced echelon form of the augmented matrix for the system. is the matrix

Math 314H EXAM I. 1. (28 points) The row reduced echelon form of the augmented matrix for the system. is the matrix Math 34H EXAM I Do all of the problems below. Point values for each of the problems are adjacent to the problem number. Calculators may be used to check your answer but not to arrive at your answer. That

More information

Glossary of Linear Algebra Terms. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB

Glossary of Linear Algebra Terms. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB Glossary of Linear Algebra Terms Basis (for a subspace) A linearly independent set of vectors that spans the space Basic Variable A variable in a linear system that corresponds to a pivot column in the

More information

Linear Algebra II Lecture 8

Linear Algebra II Lecture 8 Linear Algebra II Lecture 8 Xi Chen 1 1 University of Alberta October 10, 2014 Outline 1 2 Definition Let T 1 : V W and T 2 : V W be linear transformations between two vector spaces V and W over R. Then

More information

MATH2210 Notebook 3 Spring 2018

MATH2210 Notebook 3 Spring 2018 MATH2210 Notebook 3 Spring 2018 prepared by Professor Jenny Baglivo c Copyright 2009 2018 by Jenny A. Baglivo. All Rights Reserved. 3 MATH2210 Notebook 3 3 3.1 Vector Spaces and Subspaces.................................

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

Exam in TMA4110 Calculus 3, June 2013 Solution

Exam in TMA4110 Calculus 3, June 2013 Solution Norwegian University of Science and Technology Department of Mathematical Sciences Page of 8 Exam in TMA4 Calculus 3, June 3 Solution Problem Let T : R 3 R 3 be a linear transformation such that T = 4,

More information

Lecture 13: Orthogonal projections and least squares (Section ) Thang Huynh, UC San Diego 2/9/2018

Lecture 13: Orthogonal projections and least squares (Section ) Thang Huynh, UC San Diego 2/9/2018 Lecture 13: Orthogonal projections and least squares (Section 3.2-3.3) Thang Huynh, UC San Diego 2/9/2018 Orthogonal projection onto subspaces Theorem. Let W be a subspace of R n. Then, each x in R n can

More information

Math 353, Practice Midterm 1

Math 353, Practice Midterm 1 Math 353, Practice Midterm Name: This exam consists of 8 pages including this front page Ground Rules No calculator is allowed 2 Show your work for every problem unless otherwise stated Score 2 2 3 5 4

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

Section 1.5. Solution Sets of Linear Systems

Section 1.5. Solution Sets of Linear Systems Section 1.5 Solution Sets of Linear Systems Plan For Today Today we will learn to describe and draw the solution set of an arbitrary system of linear equations Ax = b, using spans. Ax = b Recall: the solution

More information

4 Chapter 4 Lecture Notes. Vector Spaces and Subspaces

4 Chapter 4 Lecture Notes. Vector Spaces and Subspaces Math 2040 Matrix Theory and Linear Algebra II 4 hapter 4 Lecture Notes. Vector Spaces and Subspaces 4.1 Vector Spaces and Subspaces 1. Notation: The symbol means the empty set. The symbol means is an element

More information

MATH 260 LINEAR ALGEBRA EXAM III Fall 2014

MATH 260 LINEAR ALGEBRA EXAM III Fall 2014 MAH 60 LINEAR ALGEBRA EXAM III Fall 0 Instructions: the use of built-in functions of your calculator such as det( ) or RREF is permitted ) Consider the table and the vectors and matrices given below Fill

More information

MTH 362: Advanced Engineering Mathematics

MTH 362: Advanced Engineering Mathematics MTH 362: Advanced Engineering Mathematics Lecture 5 Jonathan A. Chávez Casillas 1 1 University of Rhode Island Department of Mathematics September 26, 2017 1 Linear Independence and Dependence of Vectors

More information

Midterm 1 Solutions Math Section 55 - Spring 2018 Instructor: Daren Cheng

Midterm 1 Solutions Math Section 55 - Spring 2018 Instructor: Daren Cheng Midterm 1 Solutions Math 20250 Section 55 - Spring 2018 Instructor: Daren Cheng #1 Do the following problems using row reduction. (a) (6 pts) Let A = 2 1 2 6 1 3 8 17 3 5 4 5 Find bases for N A and R A,

More information

2. Every linear system with the same number of equations as unknowns has a unique solution.

2. Every linear system with the same number of equations as unknowns has a unique solution. 1. For matrices A, B, C, A + B = A + C if and only if A = B. 2. Every linear system with the same number of equations as unknowns has a unique solution. 3. Every linear system with the same number of equations

More information

1. What is the determinant of the following matrix? a 1 a 2 4a 3 2a 2 b 1 b 2 4b 3 2b c 1. = 4, then det

1. What is the determinant of the following matrix? a 1 a 2 4a 3 2a 2 b 1 b 2 4b 3 2b c 1. = 4, then det What is the determinant of the following matrix? 3 4 3 4 3 4 4 3 A 0 B 8 C 55 D 0 E 60 If det a a a 3 b b b 3 c c c 3 = 4, then det a a 4a 3 a b b 4b 3 b c c c 3 c = A 8 B 6 C 4 D E 3 Let A be an n n matrix

More information

(v, w) = arccos( < v, w >

(v, w) = arccos( < v, w > MA322 Sathaye Notes on Inner Products Notes on Chapter 6 Inner product. Given a real vector space V, an inner product is defined to be a bilinear map F : V V R such that the following holds: For all v

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

7. Dimension and Structure.

7. Dimension and Structure. 7. Dimension and Structure 7.1. Basis and Dimension Bases for Subspaces Example 2 The standard unit vectors e 1, e 2,, e n are linearly independent, for if we write (2) in component form, then we obtain

More information

4.9 The Rank-Nullity Theorem

4.9 The Rank-Nullity Theorem For Problems 7 10, use the ideas in this section to determine a basis for the subspace of R n spanned by the given set of vectors. 7. {(1, 1, 2), (5, 4, 1), (7, 5, 4)}. 8. {(1, 3, 3), (1, 5, 1), (2, 7,

More information

We see that this is a linear system with 3 equations in 3 unknowns. equation is A x = b, where

We see that this is a linear system with 3 equations in 3 unknowns. equation is A x = b, where Practice Problems Math 35 Spring 7: Solutions. Write the system of equations as a matrix equation and find all solutions using Gauss elimination: x + y + 4z =, x + 3y + z = 5, x + y + 5z = 3. We see that

More information

Math Final December 2006 C. Robinson

Math Final December 2006 C. Robinson Math 285-1 Final December 2006 C. Robinson 2 5 8 5 1 2 0-1 0 1. (21 Points) The matrix A = 1 2 2 3 1 8 3 2 6 has the reduced echelon form U = 0 0 1 2 0 0 0 0 0 1. 2 6 1 0 0 0 0 0 a. Find a basis for the

More information

(v, w) = arccos( < v, w >

(v, w) = arccos( < v, w > MA322 F all203 Notes on Inner Products Notes on Chapter 6 Inner product. Given a real vector space V, an inner product is defined to be a bilinear map F : V V R such that the following holds: For all v,

More information

Department of Aerospace Engineering AE602 Mathematics for Aerospace Engineers Assignment No. 4

Department of Aerospace Engineering AE602 Mathematics for Aerospace Engineers Assignment No. 4 Department of Aerospace Engineering AE6 Mathematics for Aerospace Engineers Assignment No.. Decide whether or not the following vectors are linearly independent, by solving c v + c v + c 3 v 3 + c v :

More information

6 Basis. 6.1 Introduction

6 Basis. 6.1 Introduction 6 Basis 6 Introduction If x, e, and e 2 are as pictured, then using the geometrical rules for scaling and adding vectors we see that x = 7e +4e 2 We say that x has e -coordinate 7 and e 2 -coordinate 4

More information

MA 265 FINAL EXAM Fall 2012

MA 265 FINAL EXAM Fall 2012 MA 265 FINAL EXAM Fall 22 NAME: INSTRUCTOR S NAME:. There are a total of 25 problems. You should show work on the exam sheet, and pencil in the correct answer on the scantron. 2. No books, notes, or calculators

More information

1. Let m 1 and n 1 be two natural numbers such that m > n. Which of the following is/are true?

1. Let m 1 and n 1 be two natural numbers such that m > n. Which of the following is/are true? . Let m and n be two natural numbers such that m > n. Which of the following is/are true? (i) A linear system of m equations in n variables is always consistent. (ii) A linear system of n equations in

More information

I. Multiple Choice Questions (Answer any eight)

I. Multiple Choice Questions (Answer any eight) Name of the student : Roll No : CS65: Linear Algebra and Random Processes Exam - Course Instructor : Prashanth L.A. Date : Sep-24, 27 Duration : 5 minutes INSTRUCTIONS: The test will be evaluated ONLY

More information

MATH 2360 REVIEW PROBLEMS

MATH 2360 REVIEW PROBLEMS MATH 2360 REVIEW PROBLEMS Problem 1: In (a) (d) below, either compute the matrix product or indicate why it does not exist: ( )( ) 1 2 2 1 (a) 0 1 1 2 ( ) 0 1 2 (b) 0 3 1 4 3 4 5 2 5 (c) 0 3 ) 1 4 ( 1

More information

1. TRUE or FALSE. 2. Find the complete solution set to the system:

1. TRUE or FALSE. 2. Find the complete solution set to the system: TRUE or FALSE (a A homogenous system with more variables than equations has a nonzero solution True (The number of pivots is going to be less than the number of columns and therefore there is a free variable

More information

Elementary Linear Algebra Review for Exam 2 Exam is Monday, November 16th.

Elementary Linear Algebra Review for Exam 2 Exam is Monday, November 16th. Elementary Linear Algebra Review for Exam Exam is Monday, November 6th. The exam will cover sections:.4,..4, 5. 5., 7., the class notes on Markov Models. You must be able to do each of the following. Section.4

More information

MODULE 8 Topics: Null space, range, column space, row space and rank of a matrix

MODULE 8 Topics: Null space, range, column space, row space and rank of a matrix MODULE 8 Topics: Null space, range, column space, row space and rank of a matrix Definition: Let L : V 1 V 2 be a linear operator. The null space N (L) of L is the subspace of V 1 defined by N (L) = {x

More information

LINEAR ALGEBRA REVIEW

LINEAR ALGEBRA REVIEW LINEAR ALGEBRA REVIEW SPENCER BECKER-KAHN Basic Definitions Domain and Codomain. Let f : X Y be any function. This notation means that X is the domain of f and Y is the codomain of f. This means that for

More information

Linear Equations in Linear Algebra

Linear Equations in Linear Algebra 1 Linear Equations in Linear Algebra 1.4 THE MATRIX EQUATION A = b MATRIX EQUATION A = b m n Definition: If A is an matri, with columns a 1, n, a n, and if is in, then the product of A and, denoted by

More information

Rank and Nullity. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Rank and Nullity. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Rank and Nullity MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Objectives We have defined and studied the important vector spaces associated with matrices (row space,

More information

MATH 20F: LINEAR ALGEBRA LECTURE B00 (T. KEMP)

MATH 20F: LINEAR ALGEBRA LECTURE B00 (T. KEMP) MATH 20F: LINEAR ALGEBRA LECTURE B00 (T KEMP) Definition 01 If T (x) = Ax is a linear transformation from R n to R m then Nul (T ) = {x R n : T (x) = 0} = Nul (A) Ran (T ) = {Ax R m : x R n } = {b R m

More information

Linear Algebra Exam 1 Spring 2007

Linear Algebra Exam 1 Spring 2007 Linear Algebra Exam 1 Spring 2007 March 15, 2007 Name: SOLUTION KEY (Total 55 points, plus 5 more for Pledged Assignment.) Honor Code Statement: Directions: Complete all problems. Justify all answers/solutions.

More information

MTH 35, SPRING 2017 NIKOS APOSTOLAKIS

MTH 35, SPRING 2017 NIKOS APOSTOLAKIS MTH 35, SPRING 2017 NIKOS APOSTOLAKIS 1. Linear independence Example 1. Recall the set S = {a i : i = 1,...,5} R 4 of the last two lectures, where a 1 = (1,1,3,1) a 2 = (2,1,2, 1) a 3 = (7,3,5, 5) a 4

More information

Math 308 Practice Test for Final Exam Winter 2015

Math 308 Practice Test for Final Exam Winter 2015 Math 38 Practice Test for Final Exam Winter 25 No books are allowed during the exam. But you are allowed one sheet ( x 8) of handwritten notes (back and front). You may use a calculator. For TRUE/FALSE

More information

Lecture 3: Linear Algebra Review, Part II

Lecture 3: Linear Algebra Review, Part II Lecture 3: Linear Algebra Review, Part II Brian Borchers January 4, Linear Independence Definition The vectors v, v,..., v n are linearly independent if the system of equations c v + c v +...+ c n v n

More information

Linear Algebra Final Exam Study Guide Solutions Fall 2012

Linear Algebra Final Exam Study Guide Solutions Fall 2012 . Let A = Given that v = 7 7 67 5 75 78 Linear Algebra Final Exam Study Guide Solutions Fall 5 explain why it is not possible to diagonalize A. is an eigenvector for A and λ = is an eigenvalue for A diagonalize

More information