Math 213 Calculus III Practice Exam 2 Solutions Fall 2002

Similar documents
Math 113 Calculus III Final Exam Practice Problems Spring 2003

f xx (x, y) = 6 + 6x f xy (x, y) = 0 f yy (x, y) = y In general, the quantity that we re interested in is

REVIEW I MATH 254 Calculus IV. Exam I (Friday, April 29) will cover sections

Calculus III. Math 233 Spring In-term exam April 11th. Suggested solutions

Math 126 Winter CHECK that your exam contains 8 problems.

University of California, Berkeley

. Tutorial Class V 3-10/10/2012 First Order Partial Derivatives;...

Multivariate Calculus: Review Problems for Examination Two

Multivariate Calculus Review Problems for Examination Two

Practice problems from old exams for math 233 William H. Meeks III December 21, 2009

What you will learn today

Daily WeBWorK, #1. This means the two planes normal vectors must be multiples of each other.

MATH 261 FALL 2000 FINAL EXAM INSTRUCTIONS. 1. This test booklet has 14 pages including this one. There are 25 questions, each worth 8 points.

Gradient and Directional Derivatives

Worksheet 2.7: Critical Points, Local Extrema, and the Second Derivative Test

x 6 + λ 2 x 6 = for the curve y = 1 2 x3 gives f(1, 1 2 ) = λ actually has another solution besides λ = 1 2 = However, the equation λ

Curves, Tangent Planes, and Differentials ( ) Feb. 26, 2012 (Sun) Lecture 9. Partial Derivatives: Signs on Level Curves, Tangent

Math 265 Exam 3 Solutions

6. Find the equation of the plane that passes through the point (-1,2,1) and contains the line x = y = z.

Math 213 Exam 2. Each question is followed by a space to write your answer. Please write your answer neatly in the space provided.

Date: 16 July 2016, Saturday Time: 14:00-16:00 STUDENT NO:... Math 102 Calculus II Midterm Exam II Solutions TOTAL. Please Read Carefully:

Functions of Two variables.

Directional Derivatives and the Gradient Vector Part 2

Math 126 Final Examination Autumn CHECK that your exam contains 9 problems on 10 pages.

Math Exam III Review

LECTURE 18 - OPTIMIZATION

Solution of final examination

302 CHAPTER 3. FUNCTIONS OF SEVERAL VARIABLES. 4. Function of several variables, their domain. 6. Limit of a function of several variables

Solution 2. ((3)(1) (2)(1), (4 3), (4)(2) (3)(3)) = (1, 1, 1) D u (f) = (6x + 2yz, 2y + 2xz, 2xy) (0,1,1) = = 4 14

The following information is for reviewing the material since Exam 3:

Constrained Optimization and Lagrange Multipliers

(c) 0 (d) (a) 27 (b) (e) x 2 3x2

Math 52 Final Exam March 16, 2009

we wish to minimize this function; to make life easier, we may minimize

Directional Derivatives. Directional Derivatives. Directional Derivatives. Directional Derivatives. Directional Derivatives. Directional Derivatives

MAT203 OVERVIEW OF CONTENTS AND SAMPLE PROBLEMS

Directional Derivatives and the Gradient Vector Part 2

AP * Calculus Review. Area and Volume

Surfaces and Integral Curves

Tangent Planes/Critical Points

Quiz problem bank. Quiz 1 problems. 1. Find all solutions (x, y) to the following:

Introduction to PDEs: Notation, Terminology and Key Concepts

Name: Class: Date: 1. Use Lagrange multipliers to find the maximum and minimum values of the function subject to the given constraint.

AP Calculus AB Unit 2 Assessment

Background for Surface Integration

Lecture 15. Lecturer: Prof. Sergei Fedotov Calculus and Vectors. Length of a Curve and Parametric Equations

Math 21a Tangent Lines and Planes Fall, What do we know about the gradient f? Tangent Lines to Curves in the Plane.

Chapter 5 Partial Differentiation

MA 114 Worksheet #17: Average value of a function

Review 1. Richard Koch. April 23, 2005

14.6 Directional Derivatives and the Gradient Vector

Chapter 15 Vector Calculus

CCNY Math Review Chapter 2: Functions

Chapter 15: Functions of Several Variables

Lagrange Multipliers. Lagrange Multipliers. Lagrange Multipliers. Lagrange Multipliers. Lagrange Multipliers. Lagrange Multipliers

7/26/2018 SECOND HOURLY PRACTICE V Maths 21a, O.Knill, Summer 2018

Section 4.2 selected answers Math 131 Multivariate Calculus D Joyce, Spring 2014

= w. w u. u ; u + w. x x. z z. y y. v + w. . Remark. The formula stated above is very important in the theory of. surface integral.

Exam in Calculus. Wednesday June 1st First Year at The TEK-NAT Faculty and Health Faculty

Math 241, Final Exam. 12/11/12.

Math 5BI: Problem Set 2 The Chain Rule

Equation of tangent plane: for implicitly defined surfaces section 12.9

Calculus 234. Problems. May 15, 2003

LINEAR ALGEBRA AND VECTOR ANALYSIS MATH 22A

Linear and quadratic Taylor polynomials for functions of several variables.

Math Exam 2a. 1) Take the derivatives of the following. DO NOT SIMPLIFY! 2 c) y = tan(sec2 x) ) b) y= , for x 2.

Math 21a Homework 22 Solutions Spring, 2014

3.3 Optimizing Functions of Several Variables 3.4 Lagrange Multipliers

8(x 2) + 21(y 1) + 6(z 3) = 0 8x + 21y + 6z = 55.

MATH 19520/51 Class 6

Exam 1 Review. MATH Intuitive Calculus Fall Name:. Show your reasoning. Use standard notation correctly.

Calculators ARE NOT Permitted On This Portion Of The Exam 28 Questions - 55 Minutes

MATH. 2153, Spring 16, MWF 12:40 p.m. QUIZ 1 January 25, 2016 PRINT NAME A. Derdzinski Show all work. No calculators. The problem is worth 10 points.

Practice problems. 1. Given a = 3i 2j and b = 2i + j. Write c = i + j in terms of a and b.

Curves: We always parameterize a curve with a single variable, for example r(t) =

True/False. MATH 1C: SAMPLE EXAM 1 c Jeffrey A. Anderson ANSWER KEY

Functions of Several Variables

Chapter 10 Homework: Parametric Equations and Polar Coordinates

14.5 Directional Derivatives and the Gradient Vector

11/1/2017 Second Hourly Practice 11 Math 21a, Fall Name:

d f(g(t), h(t)) = x dt + f ( y dt = 0. Notice that we can rewrite the relationship on the left hand side of the equality using the dot product: ( f

Kevin James. MTHSC 206 Section 14.5 The Chain Rule

13.1. Functions of Several Variables. Introduction to Functions of Several Variables. Functions of Several Variables. Objectives. Example 1 Solution

University of Saskatchewan Department of Mathematics & Statistics MATH Final Instructors: (01) P. J. Browne (03) B. Friberg (05) H.

MATH 104 Sample problems for first exam - Fall MATH 104 First Midterm Exam - Fall (d) 256 3

30. Constrained Optimization

1 Vector Functions and Space Curves

= x i + y j + z k. div F = F = P x + Q. y + R

Second Midterm Exam Math 212 Fall 2010

PRACTICE FINAL - MATH 1210, Spring 2012 CHAPTER 1

Direction Fields; Euler s Method

Partial Derivatives (Online)

This exam will be cumulative. Consult the review sheets for the midterms for reviews of Chapters

MATH 31A HOMEWORK 9 (DUE 12/6) PARTS (A) AND (B) SECTION 5.4. f(x) = x + 1 x 2 + 9, F (7) = 0

Parametric Surfaces. Substitution

Math 253, Section 102, Fall 2006 Practice Final Solutions

Topic 5.1: Line Elements and Scalar Line Integrals. Textbook: Section 16.2

Exam 2 Preparation Math 2080 (Spring 2011) Exam 2: Thursday, May 12.

The Divergence Theorem

Quiz 6 Practice Problems

Transcription:

Math 13 Calculus III Practice Exam Solutions Fall 00 1. Let g(x, y, z) = e (x+y) + z (x + y). (a) What is the instantaneous rate of change of g at the point (,, 1) in the direction of the origin? We want the directional derivative of g at (,, 1) in the direction of the origin. A vector in this direction is i + j k, and a unit vector in this direction is u = 1 9 ( i + j k) = ( 3i + 3j 1 ) 3k. The gradient of g is grad g(x, y, z) = and in particular ( (x + y)e (x+y) + z ) ( i + (x + y)e (x+y) + z ) j + (z(x + y)) k, grad g(,, 1) = i + j. Then the instantaneous rate of change of g in the direction u at the point (,, 1) is ( ) ( g u (,, 1) = grad g(,, 1) u = i + j 3 i + 3 j 1 ) 3 k = 0. (b) Suppose that a piece of fruit is sitting on a table in a room, and at each point (x, y, z) in the space within the room, g(x, y, z) gives the strength of the odor of the fruit. Furthermore, suppose that a certain bug always flies in the direction in which the fruit odor increases fastest. Suppose also that the bug always flies with a speed of feet/second. What is the velocity vector of the bug when it is at the position (,, 1)? Since the bug flies in the direction in which the fruit odor increases fastest, it flies in the direction of grad g. It always has a speed of, so the velocity vector at (,, 1) is grad g(,, 1) grad g(,, 1) = ( i + j).. The path of a particle in space is given by the functions x(t) = t, y(t) = cos(t), and z(t) = sin(t). Suppose the temperature in this space is given by a function H(x, y, z). (a) Find dh, the rate of change of the temperature at the particle s position. (Since the actual function H(x, y, z) is not given, your answer will be in terms of derivatives of H.) dh = H dx x + H dy y + H dz z = H H H x sin t y + cos t z (b) Suppose we know that at all points, H x positive, zero, or negative? At t = 0, dh = H x + H z > 0. H > 0, y H < 0 and z > 0. At t = 0, is dh 1

3. Let f(x, y) = x 3 xy + cos(π(x + y)). (a) Find a vector normal to the level curve f(x, y) = 1 at the point where x = 1, y = 1. The gradient of f is normal to the level curve at each point. We find grad f(x, y) = (3x y π sin(π(x + y))) i + ( x π sin(π(x + y))) j, and grad f(1, 1) = i j. (b) Find the equation of the line tangent to the level curve f(x, y) = 1 at the point where x = 1, y = 1. The line is (x 1) (y 1) = 0, or x y = 1. (c) Find a vector normal to the graph z = f(x, y) at the point x = 1, y = 1. The graph is the level surface g(x, y, z) = 0 of the function g(x, y, z) = f(x, y) z. The gradient of g is normal to the level surface at each point. We have grad g(x, y, z) = grad f(x, y) k. Now f(1, 1) = 1, so a vector normal to the graph at (1, 1, 1) is grad g(1, 1, 1) = grad f(1, 1) k = i j k. (d) Find the equation of the plane tangent to the graph z = f(x, y) at the point x = 1, y = 1. The plane is (x 1) (y 1) (z 1) = 0, or x y z = 0. 4. Let f(x, y) = (x y) 3 + xy + x y. (a) Find the linear approximation L(x, y) near the point (1, ). First get the numbers: f(1, ) = 1 + 4 + 1 =, f x (x, y) = 3(x y) + y + x, f x (1, ) = 3 + 4 + = 9, f y (x, y) = 3(x y) + x 1, f y (1, ) = 3 + 1 =. Then L(x, y) = f(1, ) + f x (1, )(x 1) + f y (1, )(y ) = + 9(x 1) (y ). (b) Find the quadratic approximation Q(x, y) near the point (1, ). We need some more numbers: f xx (x, y) = 6(x y) +, f xx (1, ) = 6 + = 4, f xy (x, y) = 6(x y) +, f xy (1, ) = 6 + = 8, f yy (x, y) = 6(x y), f xy (1, ) = 6. Then Q(x, y) = L(x, y) + f xx(1, ) (x 1) + f xy (1, )(x 1)(y ) + f yy(1, ) (y ) = + 9(x 1) (y ) (x 1) + 8(x 1)(y ) 3(y ).

5. For each of the following functions, determine the set of points where the function is not differentiable. Briefly explain how you know it is not differentiable; use a picture if it helps. (You do not have to prove that it is not differentiable; just identify the set of points based on your understanding of what differentiable means.) (a) f(x, y) = x + y 1 This function is not differentiable on the circle x + y = 1. The graph has a corner at these points. (b) f(x, y) = (x + y ) 1/4 This function is not differentiable at the origin. Consider the cross section y = 0: f(x, 0) = (x ) 1/4 = x. The graph has a cusp (i.e. a point) at x = 0. (c) f(x, y) = e x +y This function is the composition of polynomials and the exponential function, so it is differentiable everywhere. (d) f(x, y) = x3 xy + 1 x y This function is not differentiable at points where the denominator is zero; that is, where x = y. This gives the lines y = x and y = x. 6. An assortment of TRUE/FALSE or short answer questions: (a) TRUE or FALSE: If f is differentiable at (0, 0), then f is continuous at (0, 0). TRUE. See the middle box on page 69. (b) TRUE or FALSE: If f is a continuous function defined on the region x + y 9, then f has a maximum value and a minimum value in this region. TRUE. Since f is continuous, and the region is closed and bounded, Theorem 15.1 (the Extreme Value Theorem, page 716) shows that f has a global maximum and a global minimum in the region. (c) TRUE or FALSE: If f x (0, 0) exists, and f y (0, 0) exists, then f is differentiable at (0, 0). FALSE. f(x, y) = x 1/3 y 1/3 is a counter-example (see Example 3, page 691, or your notes). (d) TRUE or FALSE: If f is differentiable at (0, 0), then the tangent plane to the graph of f at (0, 0) is given by z = f(0, 0) + f x (0, 0)x + f y (0, 0)y. TRUE. See Example 1, page 690, and the comment just above Example 1. (e) Give an example of a function f(x, y) for which (0, 0) is a local minimum, but for which the second derivative test fails to determine this classification. f(x, y) = x 4 + y 4 (see Example 7, page 708, or your notes). (f) Give an example of a function g(x, y) which is differentiable everywhere except along the line y = x. g(x, y) = x y. The graph consists of two planes (z = x y if x y, and z = y x if x < y) that meet in a corner along y = x. 3

(g) Let H(x, y) = x y + xy, and suppose that x and y are both functions that depend on t. Express dh dh = H dx x + H dy y in terms of x, y, dx and dy. dx dy = (x + y) + ( y + x) 7. Suppose f is a differentiable function such that (a) Find gradf(1, 3). f(1, 3) = 1, f x (1, 3) =, f y (1, 3) = 4, f xx (1, 3) =, f xy (1, 3) = 1, and f yy (1, 3) = 4. gradf(1, 3) = f x (1, 3) i + f y (1, 3) j = i + 4 j (b) Find a vector in the plane that is perpendicular to the contour line f(x, y) = 1 at the point (1, 3). i + 4 i (from (a); the gradient vector at a point is perpendicular to the contour line through that point) (c) Find a vector that is perpendicular to the surface z = f(x, y) (i.e. the graph of f) at the point (1, 3, 1). The graph is the level surface g(x, y, z) = 0 of the function g(x, y, z) = f(x, y) z. The gradient of g is normal to the level surface at each point. We have grad g(x, y, z) = grad f(x, y) k. Now f(1, 3) = 1, so a vector normal to the graph at (1, 3, 1) is grad g(1, 3, 1) = grad f(1, 3) k = i + 4 j k. (d) At the point (1, 3), what is the rate of change of f in the direction i + j? u = ( i + j)/ is a unit vector in the direction of i + j. The rate of change of f in this direction is f u (1, 3) = gradf(1, 3) u = ( i + 4 j) ( i + j)/ = 6/ = 3. (e) Use a quadratic approximation to estimate f(1., 3.3). Near (1, 3), we have f(x, y) f(1, 3)+f x (1, 3)(x 1) + f y (1, 3)(y 3)+ f xx (1, 3) (x 1) + f xy (1, 3)(x 1)(y 3) + f yy(1, 3) (y 3). So f(1., 3.3) 1 + ()(0.) + (4)(0.3) + (/)(0.) + ( 1)(0.)(0.3) + (4/)(0.3) =.76. 4

8. For each of the following functions, find and classify the critical points. (a) f(x, y) = x 3 x + xy + y f x (x, y) = 3x x + y and f y (x, y) = x + 4y. We must solve (i) 3x x + y = 0 and (ii) x + 4y = 0. (ii) gives us y = x/, and substituting this into (i) gives 3x 3x = 0. This gives x = 0 or x = 1. If x = 0 then y = 0, and if x = 1 then y = 1/. So the critical points are (0, 0) and (1, 1/). For the second derivative test, we need f xx (x, y) = 6x, f xy (x, y) =, and f yy (x, y) = 4. At (0, 0), D = f xx (0, 0)f yy (0, 0) f xy (0, 0) = ( )(4) = 1 < 0, so (0, 0) is a saddle point. At (1, 1/), D = f xx (1, 1/)f yy (1, 1/) f xy (1, 1/) = (4)(4) = 1 > 0, and f xx (1, 1/) = 4 > 0, so (1, 1/) is a local minimum. (b) g(x, y) = (x 1) + y g x (x, y) = x 1, and g (x 1) y(x, y) = +y y. Note that the denominators are zero (x 1) +y when x = 1 and y = 0. Therefore g x and g y are not defined there, so (1, 0) is a critical point. Solving g x = 0 and g y = 0 does not give any more points, so the only critical point is (1, 0). This function is not differentiable at (1, 0), so we can not use the second derivative test. However, we recognize the shape of the graph: it is a cone, and the point of the cone is at (1, 0). (See, for example, Example 4 on page 578; the cone in this problem has been shifted to (1, 0).) Therefore (1, 0) is a local (and global) minimum. (c) h(x, y) = e x+y + x + y h x (x, y) = e x+y + 1, and h y (x, y) = e x+y + y. To find the critical points, we must solve (i) e x+y + 1 = 0 and (ii) e x+y + y = 0. First (i) gives us e x+y = 1, which implies x + y = 0, so y = x. Substitute this into (ii) to get 1 + y = 0, and therefore y = 1/. So the only critical point is ( 1/, 1/). We need h xx (x, y) = e x+y, h xy (x, y) = e x+y, and h yy (x, y) = e x+y +. At ( 1/, 1/), we have D = h xx ( 1/, 1/)h yy ( 1/, 1/) h xy ( 1/, 1/) = (1)(3) ( 1) = > 0, and h xx ( 1/, 1/) = 1 > 0, so ( 1/, 1/) is a local minimum. 5

(d) r(x, y) = (x y)(x + y)x (Hint: Consider the contour lines r(x, y) = 0.) Let s ignore the hint for the moment. Let s rewrite r(x, y) = x 3 xy. We have r x (x, y) = 3x y and r y (x, y) = xy. We must solve (i) 3x y = 0 and (ii) xy = 0. But (ii) implies that either x = 0 or y = 0. If x = 0, then (i) implies y = 0. On the other hand, if y = 0, then (i) implies x = 0. Thus the only critical point is (0, 0). We need r xx (x, y) = 6x, r xy (x, y) = y, and r yy (x, y) = x. At (0, 0), we have D = r xx (0, 0)r yy (0, 0) r xy (0, 0) = 0. So the second derivative test does not tell us the shape of the graph near (0, 0). Now let s use the hint. Consider the contour lines given by r(x, y) = 0. This is the set of points where (x y)(x+y)x = 0. This is three lines through the point (0, 0): y = x, y = x, and x = 0. Since these are the lines where r = 0, they are the boundaries of the regions where r > 0 and r < 0. Since the three lines all go through (0, 0), they separate the plane into six wedge-shaped regions, and the sign of r alternates from region to region (i.e. there are three regions where r > 0 and three regions where r < 0). In other words, the shape of the graph is a monkey saddle. 6