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

Similar documents
Math 110: Worksheet 3

Math 235: Linear Algebra

Math 4377/6308 Advanced Linear Algebra

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

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

MATH 1553, SPRING 2018 SAMPLE MIDTERM 2 (VERSION B), 1.7 THROUGH 2.9

Math 353, Practice Midterm 1

2018 Fall 2210Q Section 013 Midterm Exam II Solution

Math 2331 Linear Algebra

Lecture 03. Math 22 Summer 2017 Section 2 June 26, 2017

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

MATH 2360 REVIEW PROBLEMS

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

Solution: (a) S 1 = span. (b) S 2 = R n, x 1. x 1 + x 2 + x 3 + x 4 = 0. x 4 Solution: S 5 = x 2. x 3. (b) The standard basis vectors

Math 369 Exam #2 Practice Problem Solutions

80 min. 65 points in total. The raw score will be normalized according to the course policy to count into the final score.

Midterm solutions. (50 points) 2 (10 points) 3 (10 points) 4 (10 points) 5 (10 points)

Math 308 Practice Test for Final Exam Winter 2015

Carleton College, winter 2013 Math 232, Solutions to review problems and practice midterm 2 Prof. Jones 15. T 17. F 38. T 21. F 26. T 22. T 27.

Linear Algebra Exam 1 Spring 2007

Math 3191 Applied Linear Algebra

Math 115A: Homework 4

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

MATH 235. Final ANSWERS May 5, 2015

Math Final December 2006 C. Robinson

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

MATH 1553 PRACTICE FINAL EXAMINATION

MTH Midterm 2 Review Questions - Solutions

Comps Study Guide for Linear Algebra

MATH2210 Notebook 3 Spring 2018

Math 217 Midterm 1. Winter Solutions. Question Points Score Total: 100

OHSX XM511 Linear Algebra: Multiple Choice Exercises for Chapter 2

Math 4377/6308 Advanced Linear Algebra

Second Exam. Math , Spring March 2015

Solutions to Math 51 Midterm 1 July 6, 2016

Linear Algebra Practice Problems

Orthogonal Projection. Hung-yi Lee

Midterm 1 Solutions, MATH 54, Linear Algebra and Differential Equations, Fall Problem Maximum Score Your Score

Fall TMA4145 Linear Methods. Exercise set Given the matrix 1 2

Math 415 Exam I. Name: Student ID: Calculators, books and notes are not allowed!

Review Notes for Midterm #2

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

5.) For each of the given sets of vectors, determine whether or not the set spans R 3. Give reasons for your answers.

MATH 1553, SPRING 2018 SAMPLE MIDTERM 1: THROUGH SECTION 1.5

Linear Algebra (Math-324) Lecture Notes

MATH 1553, C.J. JANKOWSKI MIDTERM 1

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

Math 54 HW 4 solutions

Study Guide for Linear Algebra Exam 2

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.

Math 265 Midterm 2 Review

Math 24 Winter 2010 Sample Solutions to the Midterm

8 General Linear Transformations

MATH 260 LINEAR ALGEBRA EXAM III Fall 2014

Midterm #2 Solutions

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

MA 242 LINEAR ALGEBRA C1, Solutions to First Midterm Exam

Math 102, Winter 2009, Homework 7

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

MTH 362: Advanced Engineering Mathematics

Math 314/ Exam 2 Blue Exam Solutions December 4, 2008 Instructor: Dr. S. Cooper. Name:

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

NAME MATH 304 Examination 2 Page 1

PRACTICE PROBLEMS FOR THE FINAL

MATH 110: LINEAR ALGEBRA FALL 2007/08 PROBLEM SET 6 SOLUTIONS

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

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

Linear Algebra (MATH ) Spring 2011 Final Exam Practice Problem Solutions

Math 4377/6308 Advanced Linear Algebra

MATH 304 Linear Algebra Lecture 20: Review for Test 1.

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

Math 2331 Linear Algebra

Vector Spaces 4.5 Basis and Dimension

DEPARTMENT OF MATHEMATICS

Spring 2014 Math 272 Final Exam Review Sheet

I. Multiple Choice Questions (Answer any eight)

Math 4326 Fall Exam 2 Solutions

Section 3.3. Matrix Equations

(i) [7 points] Compute the determinant of the following matrix using cofactor expansion.

Math 322. Spring 2015 Review Problems for Midterm 2

Math 205, Summer I, Week 3a (continued): Chapter 4, Sections 5 and 6. Week 3b. Chapter 4, [Sections 7], 8 and 9

Definition Suppose S R n, V R m are subspaces. A map U : S V is linear if

Solutions to practice questions for the final

Math 290, Midterm II-key

Lecture Summaries for Linear Algebra M51A

Row Space, Column Space, and Nullspace

Test 3, Linear Algebra

Math 110, Spring 2015: Midterm Solutions

Math 224, Fall 2007 Exam 3 Thursday, December 6, 2007

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

1 Last time: inverses

Name: Final Exam MATH 3320

Math 3191 Applied Linear Algebra

0 2 0, it is diagonal, hence diagonalizable)

Practice Final Exam. Solutions.

Solutions to Math 51 First Exam April 21, 2011

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

MATH 1553, JANKOWSKI MIDTERM 2, SPRING 2018, LECTURE A

Assignment 1 Math 5341 Linear Algebra Review. Give complete answers to each of the following questions. Show all of your work.

MATH 213 Linear Algebra and ODEs Spring 2015 Study Sheet for Midterm Exam. Topics

Transcription:

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 why or give a counterexample that shows why the statement is not true in every case). (1) If S is a linearly dependent set, then each vector in S is a linear combination of other vectors in S. (2) Any set containing the zero vector is linearly dependent. (3) Subsets of linearly dependent sets are linearly dependent. (4) Subsets of linearly independent sets are linearly independent. (5) Every vector space that is generated by a finite set has a basis. (6) Every vector space has a finite basis. (7) If a vector space has a finite basis, then the number of vectors in every basis is the same. (7 ) The dimension of M m n (F ) is m + n. (8) Suppose that V is a finite-dimensional vector space, that S 1 is a linearly independent subset of V, and that S 2 is a subset of V that generates V. Then S 1 cannot contain more vectors than S 2. (9) If V is a vector space having dimension n, and if S is a subset of V with n vectors, then S is linearly independent if and only if S spans V. (1) If T : V W is linear, then nullity(t ) + rank(t ) = dim(w ). 2 points 2. The first four Chebyshev polynomials are 1, x, 2x 2 1, and 4x 3 3x. These polynomials arise naturally in the study of certain important differential equations. Show that the first four Chebyshev polynomials form a basis of P 3 (R). 2 points 3. Let T : R 3 R 3 be given by T (a, b, c) = (3a, 2a + c, b). Prove that T is an isomorphism and find T 1. 2 points 4. Let T : R 3 R 2 be given by T (a, b, c) = (a b, 2c). Show that T is a linear transformation. (b) Find bases for the null space and the range of T. (c) Compute the nullity and rank of T, and verify the dimension theorem. 2 points 5. Let W 1 and W 2 be subspaces of a vector space V. Prove that W 1 + W 2 is a subspace of V that contains both W 1 and W 2. (b) Prove that any subspace of V that contains both W 1 and W 2 must also contain W 1 + W 2. Page 1 of 5 Please go to the next page...

Midterm 1 (cont.) Math 4377 (15549) / 638 (14674) (215 Spring) March 5, 215 (c) Suppose W 1 = span{u 1,, u p }, W 2 = span{v 1,, v q }. where u 1,, u p and v 1,, v q are vectors in V. Show that W 1 + W 2 = span{u 1,, u p, v 1,, v q }. 2 points 6. (BONUS PROBLEM) Let V and W be finite-dimensional vector spaces and T : V W be an isomorphism. Let V be a subspace of V. Prove that T (V ) is a subspace of W. (b) Prove that dim(v ) = dim(t (V )). Page 2 of 5 Please go to the next page...

Midterm 1 (cont.) Math 4377 (15549) / 638 (14674) (215 Spring) March 5, 215 Problem 1. (1) False. (2) True. (3), False. (4) True. (5) True. (6) False. (7) True. (7 ) False. (8) True. (9) True. (1) False. Problem 2. Let β = {1, x, 2x 2 1, 4x 3 3x} and let γ = {1, x, x 2, x 3 } be the standard ordered basis for P 3 (R). We have the coordinate vectors of β in γ as: 1 [1] γ =, [x] γ = 1, [ 1 + 2x2 ] γ = 1 2 [ 3x + 4x3 ] γ = Note that the matrix with the coordinate vectors as columns have four pivots 1 1 Q = 1 3 2 4 3 4 Then {[1] γ, [x] γ, [ 1 + 2x 2 ] γ, [ 3x + 4x 3 ] γ } is linearly independent. By Thorem 2.21, β is linearly independent. Combined with the fact that β = dim(p 3 (R)) = 4, β is a basis for P 3 (R). Page 3 of 5 Please go to the next page...

Midterm 1 (cont.) Math 4377 (15549) / 638 (14674) (215 Spring) March 5, 215 Problem 3. Let β = {e 1, e 2, e 3 } be the standard ordered basis for R 3. The matrix representation of T in β is 3 [T ] β = 2 1 1 Note that the augmented matrix 3 1 1 1/3 [[T ] β I 3 ] = 2 1 1 1 1 = [ I 3 ([T ] β ) 1] 1 1 1 2/3 1 So we have 1/3 [T ] 1 β = 1 2/3 1 By Theorem 2.18, T is invertible and [T 1 ] β = ([T ] β ) 1. We have T 1 (a, b, c) = (a/3, c, 2a/3 + b). Problem 4. Note that, in the matrix and column vector notation, we have ( ) 1 1 x R 3 T (x) = Ax, A =. 2 Then, T is linear. (b) To find the null space of T, row reduce the augmented matrix corresponding to Ax = ( ) ( ) 1 1 1 1 2 1 We have Then x 1 x 2 1 x 2 = x 2 = x 2 1 x 3 1 the null space of T = span 1 The range of T is the column space of A and we have the range of T = span {pivot columns of A} = span (c) The nullity of T is 1 and the rank of T is 2 We have Then, the dimension theorem is verified. nullity(t ) + rank(t ) = 1 + 2 = 3 = dim(r 3 ). {( ) ( )} 1, 1 Page 4 of 5 Please go to the next page...

Midterm 1 (cont.) Math 4377 (15549) / 638 (14674) (215 Spring) March 5, 215 Problem 5. W 1 +W 2 is a subspace of W : Closed under vector addition, because if u, v W 1 +W 2, then there exist u 1, v 1 W 1 and u 2, v 2 W 2 such that u = u 1 + u 2 and v = v 1 + v 2, and then u + v = u 1 + u 2 + v 1 + v 2 = (u 1 + v 1 ) + (u 2 + v 2 ) W 1 + W 2. For scalar multiplication, au = a(u 1 + u 2 ) = au 1 + au 2 W 1 + W 2. Finally, W 1 + W 2 contains since both W 1, W 2 are subspaces and therefore contain. W 1 + W 2 contains both W 1 and W 2 : Every vector in W 1 + W 2 has the form x + y with x W 1, y W 2. Set y = to obtain all vectors in W 1 and x = to obtain all vectors in W 2. That is, any vector x W 1 or y W 2 is also present in W 1 + W 2. (b) A subspace W of V that contains both W 1 and W 2 must also contain all vectors of the form x + y with x W 1, y W 2, since it is closed under addition. Therefore it contains W 1 + W 2. (c) ( ) W 1 + W 2 span{u 1,, u p, v 1,, v q }: For any u W 1 = span{u 1,, u p } and v W 2 = span{v 1,, v q }, there exist c 1,, c p and d 1,, d q such that Then u = c 1 u 1 + + c p u p, v = d 1 v 1 + + d q v q. u + v = c 1 u 1 + + c p u p + d 1 v 1 + + d q v q span{u 1,, u p, v 1,, v q } ( ) span{u 1,, u p, v 1,, v q } W 1 +W 2 : For any w span{u 1,, u p, v 1,, v q }, there exist c 1,, c p and d 1,, d q such that w = (c 1 u 1 + + c p u p ) + (d 1 v 1 + + d q v q ) W 1 + W 2 Problem 6. (BONUS PROBLEM) (1) T (V ) contains W, since V V and T ( V ) = W. (2) Let u 1, u 2 T (V ), then there exist v 1, v 2 V such that T (v 1 ) = u 1 and T (v 2 ) = u 2. Then v 1 + v 2 V, and T (V ) T (v 1 + v 2 ) = T (v 1 ) + T (v 2 ) = u 1 + u 2. (3) Similarly for scalar multiplication, let u T (V ), then there exists v V such that T (v) = u. Then av V, and T (V ) T (av) = at (v) = au. Combining (1)-(3) shows that T (V ) is a subspace of W. (a ) Let β = {u 1,, u n } be a basis for V. T being linear, we have T (V ) = {T (v), v V } = {T (a 1 u 1 + + a n u n ), a 1,, a n F } = {a 1 T (u 1 ) + + a n T (u n ), a 1,, a n F } = span{t (u 1 ),, T (u n )} Then T (V ) is a subspace of W. (b) Let β = {u 1,, u n } be a basis for V. T (β) is then a basis for T (V ) (from (a )), since it spans T (V ) and its vectors are linearly independent: a 1 T (u 1 ) + + a n T (u n ) = T (a 1 u 1 + + a n u n ) = gives a 1 u 1 + + a n u n = since T is an isomorphism, and a 1 = = a n = since β is a basis for V. Thus, n = dim(v ) = dim(t (V )). When you finish this exam, you should go back and reexamine your work for any errors that you may have made. Page 5 of 5 End of exam.