Solutions to the Calculus and Linear Algebra problems on the Comprehensive Examination of January 28, 2011

Similar documents
Solutions to the Multivariable Calculus and Linear Algebra problems on the Comprehensive Examination of January 31, 2014

1. (a) (5 points) Find the unit tangent and unit normal vectors T and N to the curve. r (t) = 3 cos t, 0, 3 sin t, r ( 3π

Answer Keys For Math 225 Final Review Problem

e x3 dx dy. 0 y x 2, 0 x 1.

235 Final exam review questions

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

NATIONAL UNIVERSITY OF SINGAPORE MA1101R

Dimension. Eigenvalue and eigenvector

MATH 115A: SAMPLE FINAL SOLUTIONS

1. For each function, find all of its critical points and then classify each point as a local extremum or saddle point.

Instructions: No books. No notes. Non-graphing calculators only. You are encouraged, although not required, to show your work.

Solutions to Sample Questions for Final Exam

PRACTICE FINAL EXAM. why. If they are dependent, exhibit a linear dependence relation among them.

Chapters 5 & 6: Theory Review: Solutions Math 308 F Spring 2015

Math 23b Practice Final Summer 2011

Jim Lambers MAT 280 Summer Semester Practice Final Exam Solution. dy + xz dz = x(t)y(t) dt. t 3 (4t 3 ) + e t2 (2t) + t 7 (3t 2 ) dt

MATH 304 Linear Algebra Lecture 23: Diagonalization. Review for Test 2.

Math Review for Exam Compute the second degree Taylor polynomials about (0, 0) of the following functions: (a) f(x, y) = e 2x 3y.

Math 114: Make-up Final Exam. Instructions:

7a3 2. (c) πa 3 (d) πa 3 (e) πa3

Definition (T -invariant subspace) Example. Example

MATH 304 Linear Algebra Lecture 33: Bases of eigenvectors. Diagonalization.

Math 350 Solutions for Final Exam Page 1. Problem 1. (10 points) (a) Compute the line integral. F ds C. z dx + y dy + x dz C

Linear Algebra Practice Problems

Page Problem Score Max Score a 8 12b a b 10 14c 6 6

MATH 0350 PRACTICE FINAL FALL 2017 SAMUEL S. WATSON. a c. b c.

LINEAR ALGEBRA REVIEW

Math 308 Practice Test for Final Exam Winter 2015

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

Remark By definition, an eigenvector must be a nonzero vector, but eigenvalue could be zero.

Solutions to Final Practice Problems Written by Victoria Kala Last updated 12/5/2015

Review problems for the final exam Calculus III Fall 2003

One side of each sheet is blank and may be used as scratch paper.

Note: Each problem is worth 14 points except numbers 5 and 6 which are 15 points. = 3 2

SOLUTIONS TO THE FINAL EXAM. December 14, 2010, 9:00am-12:00 (3 hours)

Math Final December 2006 C. Robinson

Math 322. Spring 2015 Review Problems for Midterm 2

1.1 Limits and Continuity. Precise definition of a limit and limit laws. Squeeze Theorem. Intermediate Value Theorem. Extreme Value Theorem.

EXERCISES ON DETERMINANTS, EIGENVALUES AND EIGENVECTORS. 1. Determinants

Review for the First Midterm Exam

Math 314H Solutions to Homework # 3

(a) The points (3, 1, 2) and ( 1, 3, 4) are the endpoints of a diameter of a sphere.

Math 240 Calculus III

MAT 211 Final Exam. Spring Jennings. Show your work!

Announcements Wednesday, November 01

Comps Study Guide for Linear Algebra

Linear Algebra Practice Problems

MATH 304 Linear Algebra Lecture 34: Review for Test 2.

Eigenspaces and Diagonalizable Transformations

McGill University April Calculus 3. Tuesday April 29, 2014 Solutions

Math 323 Exam 2 Sample Problems Solution Guide October 31, 2013

Math 250B Final Exam Review Session Spring 2015 SOLUTIONS

DM554 Linear and Integer Programming. Lecture 9. Diagonalization. Marco Chiarandini

Definitions for Quizzes

1. Select the unique answer (choice) for each problem. Write only the answer.

Disclaimer: This Final Exam Study Guide is meant to help you start studying. It is not necessarily a complete list of everything you need to know.

Dr. Allen Back. Nov. 5, 2014

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

1. Matrix multiplication and Pauli Matrices: Pauli matrices are the 2 2 matrices. 1 0 i 0. 0 i

Study Guide for Linear Algebra Exam 2

MAT 211 Final Exam. Fall Jennings.

Math 215 HW #9 Solutions

Remark 1 By definition, an eigenvector must be a nonzero vector, but eigenvalue could be zero.

Practice Problems for Exam 3 (Solutions) 1. Let F(x, y) = xyi+(y 3x)j, and let C be the curve r(t) = ti+(3t t 2 )j for 0 t 2. Compute F dr.

4. Linear transformations as a vector space 17

Practice problems for Exam 3 A =

Math 353, Practice Midterm 1

Chapter 5. Eigenvalues and Eigenvectors

Linear Algebra Practice Final

Calculus 2502A - Advanced Calculus I Fall : Local minima and maxima

MATH 1553, Intro to Linear Algebra FINAL EXAM STUDY GUIDE

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

x + ye z2 + ze y2, y + xe z2 + ze x2, z and where T is the

Solutions to Final Exam

MA 351 Fall 2008 Exam #3 Review Solutions 1. (2) = λ = x 2y OR x = y = 0. = y = x 2y (2x + 2) = 2x2 + 2x 2y = 2y 2 = 2x 2 + 2x = y 2 = x 2 + x

1. If the line l has symmetric equations. = y 3 = z+2 find a vector equation for the line l that contains the point (2, 1, 3) and is parallel to l.

PRACTICE PROBLEMS FOR THE FINAL

No calculators, cell phones or any other electronic devices can be used on this exam. Clear your desk of everything excepts pens, pencils and erasers.

Final EXAM Preparation Sheet

Math 210, Final Exam, Spring 2012 Problem 1 Solution. (a) Find an equation of the plane passing through the tips of u, v, and w.

MATH Spring 2011 Sample problems for Test 2: Solutions

Eigenvalues and Eigenvectors A =

Student name: Student ID: Math 265 (Butler) Midterm III, 10 November 2011

APPM 2350 Final Exam points Monday December 17, 7:30am 10am, 2018

MATH 315 Linear Algebra Homework #1 Assigned: August 20, 2018

LESSON 23: EXTREMA OF FUNCTIONS OF 2 VARIABLES OCTOBER 25, 2017

Practice Final Exam Solutions

1. In this problem, if the statement is always true, circle T; otherwise, circle F.

City Suburbs. : population distribution after m years

Mathematics 205 Solutions for HWK 23. e x2 +y 2 dxdy

MATH 221, Spring Homework 10 Solutions

MATH 52 FINAL EXAM SOLUTIONS

Contents. MATH 32B-2 (18W) (L) G. Liu / (TA) A. Zhou Calculus of Several Variables. 1 Multiple Integrals 3. 2 Vector Fields 9

Final Review Written by Victoria Kala SH 6432u Office Hours R 12:30 1:30pm Last Updated 11/30/2015

Solutions Problem Set 8 Math 240, Fall

DO NOT BEGIN THIS TEST UNTIL INSTRUCTED TO START

Jordan Canonical Form Homework Solutions

Eigenvectors. Prop-Defn

Sample Solutions of Assignment 9 for MAT3270B

Solutions to old Exam 3 problems

Transcription:

Solutions to the Calculus and Linear Algebra problems on the Comprehensive Examination of January 8, Solutions to Problems 5 are omitted since they involve topics no longer covered on the Comprehensive Examination. 6. [8 points] Let C be the boundary (oriented counterclockwise) of the region under y e x for x. Compute C xy3 dx + (xy + 3x y ) dy. Solution: Just apply Greens s Theorem. Let be the region enclosed by C; then we have: xy 3 dx + (xy + 3x y ) dy x (xy + 3x y ) y (xy3 ) da C (y + 6xy ) 6xy da y da. Now simply integrate y over : y da e x y dy dx e x y dx ex dx 4 (e4 ). ex 7. [5 points] Let V be the region in R 3 inside the sphere x + y + z and above the plane z. (a) Express the volume of V in cartesian, cylindrical and spherical coordinates. Solution: We are working with a half sphere whose projection onto the xy-plane is x + y. The answer is straightforward for cartesian coordinates: Vol x x x y dz dy dx. For cylindrical coordinates, the given constraint means r. Any θ satisfies the constraint. The top half of the sphere is z r, so the integral becomes:

π Vol r r dz dr dθ. For spherical coordinates, the constraint for ρ is ρ. Any θ satisfies the constraint. Above the plane z means φ π/. Therefore the integral is: Vol π π/ (b) Evaluate one of the integrals found in part (a). ρ sin φ dφ dρ dθ. Solution: We can choose any of these integrals to evaluate, but clearly it will be easier to use cylindrical coordinates or spherical coordinates because they involve less square root calculation. Below we give the solutions for both. For cylindrical coordinates: Vol π r π π π r dz dr dθ π r r dr dθ r r dr dθ u r, du r dr, so du r dr π π u ( du) dθ u / du dθ 3 u3/ dθ 3 dθ π 3. For spherical coordinates: Vol π π/ π π π 3 ρ3 π ρ cos φ ρ dρ dθ dθ 3 dθ π 3. ρ sin φ dφ dρ dθ π/ dρ dθ

8. [9 points] Let f(x, y) be differentiable on R. (a) State the definition of the partial derivatives f x (, ) and f y (, ). Solution: For the given function: f(h, ) f(, ) f x (, ) lim h h f(, h) f(, ) f y (, ) lim. h h (b) Suppose that f x (, ) and that the directional derivative of f at (, ) in the direction u (, ) is 5/. etermine the value of f y (, ). Solution: By the formula for the directional derivative, u f(, ) f(, ) u f x (, ) + f y (, ) where u (, ) (, ). From the given conditions we know u f(, ) 5 and f x (, ). Substituting these numbers into the above equation yields f y (, ) 3. 9. [ points] Let f(x, y) 4xy x 4 y 4. (a) Find the critical points of f(x, y). Solution: Since f is a polynomial, it is continuous. The critical points occur when f x (x, y) 4y 4x 3 f y (x, y) 4x 4y 3. Thus y x 3 and x y 3. Substituting the first equation into the second gives x (x 3 ) 3 x 9, so x 9 x x(x 8 ). Thus x or x 8, i.e., x ±. Since y x 3, we obtain the solutions x y, x y and x y Therefore the critical points are (, ), (, ) and (, ). (b) Use the second derivative test to classify the critical points as local maxima, local minima or saddle points. Solution: First compute the second derivatives. f xx (x, y) x, f xy (x, y) 4, f yy (x, y) y. (x, y) f xx (x, y)f yy (x, y) (f xy (x, y)) 44x y 6. Since (, ) 6 <, it follows from the second derivative test that the origin is a saddle point. Since (, ) 8 > and f xx (, ) <, (, ) is a local maximum. Since (, ) 8 > and f xx (, ) <, (, ) is also a local maximum. 3

. [ points] Let T : R R be a linear transformation such that T T. 3 ( ) (a) Find the matrix of T with respect to the standard basis of R. Solution: Let u and v. Notice that u + e + e v e e. Therefore we have e (u + v) e Since T is a linear transformation, (u v). ( ) 8 and T (e ) T ( (u + v)) T (u) + T (v) ( ) 8 + 3 3e 3 + e T (e ) T ( (u v)) T (u) T (v) ( ) 8 5 5e 3 e. ( ) 3 5 So the matrix representation of T is A. Thus T (w) Aw for w R. (b) What is the rank of the matrix of part (a)? Is T one-to-one? Onto? Justify your answers. 3 5 Solution: The columns and are clearly linearly independent, so the rank of the matrix A of part (a) is. Since T (v) Av, the range of T is the column space of A, and the dimension of the column space is the rank. Hence the range R(T ) of T has dimension. Since R(T ) R, it follows that R(T ) R. Thus T is onto. The rank-nullity theorem implies that dim N(T ) + dim R(T ) dim R, where N(T ) ker(t ) is the nullspace or kernel of T. Hence dim N(T ), so that N(T ) {}. This proves that T is one-to-one.. [ points] Let T : V W be linear. Also assume that v, v,..., v k form a basis of the nullspace of T and that these vectors can be extended to a basis v, v,..., v k, v k+,..., v n of V. (a) Express the dimension of the range of T in terms of n and k. Solution: According to the given information, the nullity of T is k and the dimension of V is n. Therefore by the rank-nullity theorem we get the rank of T n k, i.e. the dimension of the range of T is n k. 4

(b) Prove that T (v k+ ),..., T (v n ) are linearly independent in W. Solution: To prove T (v k+ ),..., T (v n ) are linearly independent in W, we prove that a k+ T (v k+ ) + a k+ T (v k+ ) + + a n T (v n ) implies a k+ a k+ a n. Suppose that a k+ T (v k+ ) + a k+ T (v k+ ) + + a n T (v n ). Because T is a linear transformation, it follows that a k+ T (v k+ ) + a k+ T (v k+ ) + + a n T (v n ) T (a k+ v k+ + + a n v n ). Hence a k+ v k+ + + a n v n is in the nullspace of T. Since v,..., v k forms a basis of the nullspace, there exist b,..., b k R such that a k+ v k+ + + a n v n b v + + b k v k. Therefore we get the equation: a k+ v k+ + + a n v n b v b k v k. Because v, v,..., v k, v k+,..., v n form a basis of V, these vectors are linearly independent by definition. Hence a k+ v k+ + + a n v n b v b k v k implies a k+ a k+ a n b b b k. Thereby we have shown a k+ T (v k+ ) + a k+ T (v k+ ) + + a n T (v n ) implies a k+ a k+ a n. Hence T (v k+ ),..., T (v n ) are linearly independent in W.. [ points] Let A. Find an invertible matrix Q such that Q AQ is diagonal. Solution: We first find all the eigenvalues of A, i.e., we find all possible λ R such that for each λ there exists v and Av λv. To find such values, we find which λ would make det(a λi). λ det(a λi) det λ ( λ)( λ)( λ), so λ or λ. λ 5

If λ, we find the nullspace of A: A y + z y z. Note that x and z are free variables. This gives the solutions x x y z x + z. z z It follows that that for the eigenvalue λ, the eigenspace E (that is, the nullspace of A I) has dimension with a basis consisting of the eigenvectors v and v. If λ, we find the nullspace of A I: A I x z y x z y. The only free variable is z, giving the solutions x z y z. z z Thus the eigenspace E for λ is spanned by the single eigenvector v 3. Therefore if we take Q, we should have Q AQ. (One can check that Q and that the above equation does hold.) 6