Solution to Homework 1

Size: px
Start display at page:

Download "Solution to Homework 1"

Transcription

1 Solution to Homework 1 Olena Bormashenko September, 0 Section 1.1:, 5b)d), 7b)f), 8a)b), ; Section 1.:, 5, 7, 9, 10, b)c), 1, 15b), 3 Section 1.1. In each of the following cases, find a point that is two-thirds of the distance from the first initial) point to the second terminal) point. a), 7, ), 10, 10, ) Solution: Given two points P and Q, the vector that represents the movement from P to Q is P Q. We are looking for a point A which is two thirds of the distance from P to Q this is equivalent to saying that we start at P, and go two-thirds of the way to Q. Going all the way to Q corresponds to P Q this means that going to A corresponds to going 3 P Q). In this particular case, we see that the vector corresponding to the motion from the first point to the second point is 10, 10, ), 7, ) = [1, 17, 9]. This means that the vector corresponding to going two-thirds of the way is [1, 17, 9] = [8/3, 3/3, 6] 3 Therefore, to get from P to A we need to move according to the above vector. Thus, A P = [8/3, 3/3, 6], and so A = P + [8/3, 3/3, 6] =, 7, ) + [8/3, 3/3, 6] = 16/3, 13/3, 8) b), 1, 0, 7),, 1, 9, ). Solution: Doing the same kind of calculation as in part a), we see that our point is precisely:, 1, 0, 7) +, 1, 9, ), 1, 0, 7)) 3 1

2 which simplifies to 0/3, 1, 6, 1). 5. In each of the following cases, find a unit vector in the same direction as the given vector. Is the resulting normalized)vector longer or shorter than the original? Why? b) [, 1, 0, ] Solution: In order to find a unit vector in the same direction as a given vector, just divide by the length of the vector. This makes intuitive sense: if you had a vector of length, then to get a unit vector a vector of length 1) in the same direction, you would divide by.) Furhermore, it s clear that our unit vector is longer than the original vector if and only if the vector we started with had length less than 1. Let u be our unit vector. Then, [, 1, 0, ] u = [, 1, 0, ] = [, 1, 0, ] ) [ 1 =,, 0, ] Since the length of the original vector 1, the resulting unit vector is shorter than the original vector. d) [ 1 5, 5, 1 5, 1 5, ] 5 Solution: In the same way as before, [ 1 5, 5, 1 5, 1 5, 5] u = ) ) + 1 5) + 1 5) + 5 [ 1 5, 5, 1 5, 1 5, [ 5] 1 5, 5, 1 5, 1 5, 5] = = 5 = [ 1,, 1, 1, Since the length of the original vector is is longer than the original vector. 5 5 ] ), the normalized vector 7. If x = [,, 5], y = [ 1, 0, 3], and z = [, 1, ], find the following b) y Solution: By definition, y = [ 1, 0, 3] = [, 0, 6]

3 f) x + 3 y z Solution: By definition, x + 3 y z = [,, 5] + 3[ 1, 0, 3] [, 1, ] = [, 8, 10] + [ 3, 0, 9] [16,, 8] = [ 3, 1, ] 8. Given x and y as follows, calculate x + y, x y, and y x and sketch x, y, x + y, x y in the same coordinate system. a) x = [ 1, 5], y = [, ] Solution: x + y = [ 1, 5] + [, ] = [1, 1] x y = [ 1, 5] [, ] = [ 3, 9] y x = [, ] [ 1, 5] = [3, 9] b) x = [10, ], y = [ 7, 3] Solution: x + y = [10, ] + [ 7, 3] = [3, 5] x y = [10, ] [ 7, 3] = [17, 1] y x = [ 7, 3] [10, ] = [ 17, 1]. a) Prove that the length of each vector in R n is nonnegative. Assumptions: x is a vector in R n. Need to show: x 0. Let x = [x 1, x,..., x n ]. Then, x = x 1 + x + + x n. Since squares are nonnegative, x 1 + x + + x n 0 Since the square root of a nonnegative number is defined to be nonnegative, we see that x = x 1 + x + + x n 0, so we re done. b) Prove that the only vector in R n of length 0 is the zero vector. 3

4 Section 1. Assumptions: x = 0 Need to show: x = 0 Let x = [x 1, x,..., x n ]. Then, we have that 0 = x = x x n 0 = x x n Since each of the x i is non-negative, and their sum is 0, the only way this is possible is that each is 0. Thus, x i is 0 for each i, and hence x = 0.. Show that the points A 1 9, 19, 16), A, 1, 13), and A 3 1, 3, 10) are the vertices of a right triangle. Hint: Construct vectors between the points and check for an orthogonal pair.) Solution: The vectors that represent the sides of the triangle are A 1 A, A A 3, and A 1 A 3. We had to choose between A 1 A and A A 1, etc., but this is not important.) Accordingly, they are: A 1 A = 9, 19, 16), 1, 13) = [, 7, 3] A A 3 =, 1, 13) 1, 3, 10) = [ 3,, 3] A 3 A 1 = 1, 3, 10) 9, 19, 16) = [5,, 6] Checking, the various pairs, we see that A 1 A ) A A 3 ) = [, 7, 3] [ 3,, 3] = 6 A A 3 ) A 3 A 1 ) = [ 3,, 3] [5,, 6] = 77 A 3 A 1 ) A 1 A ) = [5,, 6] [, 7, 3] = 0 Thus, the last equation shows that A 3 A 1 ) is perpendicular to A 1 A ), and therefore the triangle has a right angle at A Why isn t it true that if x, y, z R n, then x y z) = x y) z? Solution: Since y z is a scalar, the dot product x y z) is simply not defined it s impossible to calculate the dot product of a vector and a scalar. Therefore, neither left-hand side nor right-hand side are defined, so the statement is not true. 7. Does the Cancellation Law of algebra always hold for the dot product:that is, assuming that z 0, does x z = y z always imply that x = y?

5 Solution: This does not hold. The simplest example one can come up with is an example where z is perpendicular to both y and x in that case, both the dot products are 0. For example, let x = [0, 1, 1], y = [0, 1, 0] and let z = [1, 0, 0]. In that case, but x y. x z = 0 = y z 9. Prove that if x + y) x y) = 0 then x = y. Assumptions: x + y) x y) = 0 Need to show: x = y As usual, we use the assumption to show the desired result. Here, expanding things out, 0 = x + y) x y) = x x y x + x y y y = x x y y = x y using the fact that x y = y x and the identity for length in terms of the dot product. Rearranging, this yields x = y. Since the lengths are both nonnegative, we can take the square roots of both sides to conclude that x = y, as required. 10. Prove that 1 x + y + x y ) = x + y. Assumptions: No real assumptions. Need to show: 1 x + y + x y ) = x + y Here, there are no assumptions, so we just need to check that the lefthand side and the right-hand side are equal in general. Since we have squares of lengths, we rewrite everything in terms of dot products. We start from the left-hand side and manipulate it: 1 x + y + x y ) = 1 x + y) x + y) + x y) x y)) = 1 x x + x y + y y + x x x y + y y) as required. = 1 x x + y y) = x + y 5

6 . b) Prove that if x, y, z are mutually orthogonal vectors in R n, then x + y + z = x + y + z Assumptions: x, y and z are mutually orhogonal: that is, x y = 0, x z = 0, and y z = 0 Need to show: x + y + z = x + y + z Again, rewriting everything in terms of dot products: x + y + z = x + y + z) x + y + z) = x x + y y + z z + x y + y z + x z = x x + y y + z z = x + y + z using the assumption, and the identity for the length of a vector. c) Prove that x y = 1 x + y x y ). Assumptions: None. Need to show: x y = 1 x + y x y ). Using dot products once again, and starting from the right-hand side: 1 x + y x y ) = 1 x + y) x + y) x y) x y)) as required. = 1 x x + x y + y y x x x y + y y)) = 1 x y) = x y 1. Given x, y, z in R n, with x orthogonal to both y and z, prove that x is orthogonal to c 1 y + c z where c 1, c R. Assumptions: x orthogonal to both y and z: that is, x y = 0 and x z = 0. Need to show: x c 1 y + c z) = 0 The trickiest part here is writing everything down in terms of dot products! As soon as that s done, it s very easy. Using vector identities. and so we re done. x c 1 y + c z) = x c 1 y) + x c z) = c 1 x y + c x z = 0 6

7 15. Calculate proj a b in each case, and verify that b proj a b is orthogonal to a. b) a = [ 5, 3, 0], b = [3, 7, 1]. Solution: By definition, ) proj a b a b = a a Therefore, here we have proj [ 5, 3, 0] [3, 7, 1] a b = [ 5, 3, 0] 36 = 5) = 36 [ 5, 3, 0] = 3 ) [ 5, 3, 0] ) [ 5, 3, 0] [ ] 90 17, 5 17, 0 Now, verifying that b proj a b is orthogonal to a: ) [ ]) a b proj a 90 b = [ 5, 3, 0] [3, 7, 1] 17, 5 17, 0 [ = [ 5, 3, 0] 39 ] 17, 65 17, 1 3. True or False: = = 0 Since the dot product is 0, they are indeed orthogonal. a) For any vectors x and y, and any scalar d, x d y) = d x) y. TRUE: This follows from Identity ) in Theorem 1.5. b) For all x, y in R n with x 0, x y/ x y. TRUE: This follows from Cauchy-Schwarz. c) For all x, y in R n, x y x y. FALSE: In fact, the opposite of this is true, which can be shown using Triangle Inequality: x y x y. Let s provide a counterexample: let x = [1, 0] and y = [0, 1]. In that case, x y = [1, 1] =, x = 1, y = 1 7

8 and it s not true that 1 1 = 0. d) If θ is the angle between x and y in R n, and θ > π, then x y > 0. FALSE: From Theorem 1.8, x y > 0 if and only if the angle θ is acute. e) The standard unit vectors in R n are mutually orthogonal. TRUE: The standard unit vectors are e 1 = [1, 0,..., 0], e = [0, 1, 0,... ], etc., and it s easy to check that any pair of these has dot product 0. f) If proj a b = b, then a is perpendicular to b. FALSE: It can be checked that a is perpendicular to b if and only if proj a b = 0. Furthermore, proj a b = b if and only if a and b are parallel. We will not prove these statements here, but we will provide a counterexample to the assertion. Take a = b = [1, 0]. In that case, it can be checked that proj a b = b, but a and b are certainly not orthogonal. 8

Solution to Proof Questions from September 1st

Solution to Proof Questions from September 1st Solution to Proof Questions from September 1st Olena Bormashenko September 4, 2011 What is a proof? A proof is an airtight logical argument that proves a certain statement in general. In a sense, it s

More information

Dot Products. K. Behrend. April 3, Abstract A short review of some basic facts on the dot product. Projections. The spectral theorem.

Dot Products. K. Behrend. April 3, Abstract A short review of some basic facts on the dot product. Projections. The spectral theorem. Dot Products K. Behrend April 3, 008 Abstract A short review of some basic facts on the dot product. Projections. The spectral theorem. Contents The dot product 3. Length of a vector........................

More information

Linear Algebra. Alvin Lin. August December 2017

Linear Algebra. Alvin Lin. August December 2017 Linear Algebra Alvin Lin August 207 - December 207 Linear Algebra The study of linear algebra is about two basic things. We study vector spaces and structure preserving maps between vector spaces. A vector

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

EGR2013 Tutorial 8. Linear Algebra. Powers of a Matrix and Matrix Polynomial

EGR2013 Tutorial 8. Linear Algebra. Powers of a Matrix and Matrix Polynomial EGR1 Tutorial 8 Linear Algebra Outline Powers of a Matrix and Matrix Polynomial Vector Algebra Vector Spaces Powers of a Matrix and Matrix Polynomial If A is a square matrix, then we define the nonnegative

More information

Linear Algebra: Homework 3

Linear Algebra: Homework 3 Linear Algebra: Homework 3 Alvin Lin August 206 - December 206 Section.2 Exercise 48 Find all values of the scalar k for which the two vectors are orthogonal. [ ] [ ] 2 k + u v 3 k u v 0 2(k + ) + 3(k

More information

Exercise Solutions for Introduction to 3D Game Programming with DirectX 10

Exercise Solutions for Introduction to 3D Game Programming with DirectX 10 Exercise Solutions for Introduction to 3D Game Programming with DirectX 10 Frank Luna, September 6, 009 Solutions to Part I Chapter 1 1. Let u = 1, and v = 3, 4. Perform the following computations and

More information

This pre-publication material is for review purposes only. Any typographical or technical errors will be corrected prior to publication.

This pre-publication material is for review purposes only. Any typographical or technical errors will be corrected prior to publication. This pre-publication material is for review purposes only. Any typographical or technical errors will be corrected prior to publication. Copyright Pearson Canada Inc. All rights reserved. Copyright Pearson

More information

Math 32A Discussion Session Week 2 Notes October 10 and 12, 2017

Math 32A Discussion Session Week 2 Notes October 10 and 12, 2017 Math 32A Discussion Session Week 2 Notes October 10 and 12, 2017 Since we didn t get a chance to discuss parametrized lines last week, we may spend some time discussing those before moving on to the dot

More information

Brief Review of Exam Topics

Brief Review of Exam Topics Math 32A Discussion Session Week 3 Notes October 17 and 19, 2017 We ll use this week s discussion session to prepare for the first midterm. We ll start with a quick rundown of the relevant topics, and

More information

The Cross Product of Two Vectors

The Cross Product of Two Vectors The Cross roduct of Two Vectors In proving some statements involving surface integrals, there will be a need to approximate areas of segments of the surface by areas of parallelograms. Therefore it is

More information

Applied Linear Algebra in Geoscience Using MATLAB

Applied Linear Algebra in Geoscience Using MATLAB Applied Linear Algebra in Geoscience Using MATLAB Contents Getting Started Creating Arrays Mathematical Operations with Arrays Using Script Files and Managing Data Two-Dimensional Plots Programming in

More information

F F. proj cos( ) v. v proj v

F F. proj cos( ) v. v proj v Geometric Definition of Dot Product 1.2 The Dot Product Suppose you are pulling up on a rope attached to a box, as shown above. How would you find the force moving the box towards you? As stated above,

More information

Quiz 2 Practice Problems

Quiz 2 Practice Problems Quiz Practice Problems Practice problems are similar, both in difficulty and in scope, to the type of problems you will see on the quiz. Problems marked with a are for your entertainment and are not essential.

More information

MTH 2310, FALL Introduction

MTH 2310, FALL Introduction MTH 2310, FALL 2011 SECTION 6.2: ORTHOGONAL SETS Homework Problems: 1, 5, 9, 13, 17, 21, 23 1, 27, 29, 35 1. Introduction We have discussed previously the benefits of having a set of vectors that is linearly

More information

Mathematics 2203, Test 1 - Solutions

Mathematics 2203, Test 1 - Solutions Mathematics 220, Test 1 - Solutions F, 2010 Philippe B. Laval Name 1. Determine if each statement below is True or False. If it is true, explain why (cite theorem, rule, property). If it is false, explain

More information

2) If a=<2,-1> and b=<3,2>, what is a b and what is the angle between the vectors?

2) If a=<2,-1> and b=<3,2>, what is a b and what is the angle between the vectors? CMCS427 Dot product review Computing the dot product The dot product can be computed via a) Cosine rule a b = a b cos q b) Coordinate-wise a b = ax * bx + ay * by 1) If a b, a and b all equal 1, what s

More information

What you will learn today

What you will learn today What you will learn today The Dot Product Equations of Vectors and the Geometry of Space 1/29 Direction angles and Direction cosines Projections Definitions: 1. a : a 1, a 2, a 3, b : b 1, b 2, b 3, a

More information

Projection Theorem 1

Projection Theorem 1 Projection Theorem 1 Cauchy-Schwarz Inequality Lemma. (Cauchy-Schwarz Inequality) For all x, y in an inner product space, [ xy, ] x y. Equality holds if and only if x y or y θ. Proof. If y θ, the inequality

More information

Covariance and Dot Product

Covariance and Dot Product Covariance and Dot Product 1 Introduction. As you learned in Calculus III and Linear Algebra, the dot product of two vectors x = (x 1,..., x n ) and y = (y 1,..., y n ) in R n is the number n := x i y

More information

MTH 2032 SemesterII

MTH 2032 SemesterII MTH 202 SemesterII 2010-11 Linear Algebra Worked Examples Dr. Tony Yee Department of Mathematics and Information Technology The Hong Kong Institute of Education December 28, 2011 ii Contents Table of Contents

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

The Transpose of a Vector

The Transpose of a Vector 8 CHAPTER Vectors The Transpose of a Vector We now consider the transpose of a vector in R n, which is a row vector. For a vector u 1 u. u n the transpose is denoted by u T = [ u 1 u u n ] EXAMPLE -5 Find

More information

3 Scalar Product. 3.0 The Dot Product. ~v ~w := v 1 w 1 + v 2 w v n w n.

3 Scalar Product. 3.0 The Dot Product. ~v ~w := v 1 w 1 + v 2 w v n w n. 3 Scalar Product Copyright 2017, Gregory G. Smith 28 September 2017 Although vector products on R n are rare, every coordinate space R n is equipped with a binary operation that sends two vectors to a

More information

Math 241, Exam 1 Information.

Math 241, Exam 1 Information. Math 241, Exam 1 Information. 2/13/13, LC 310, 11:15-12:05. Exam 1 will be based on: Sections 12.1-12.5, 14.2. The corresponding assigned homework problems (see http://www.math.sc.edu/ boylan/sccourses/241sp13/241.html)

More information

Inner Product Spaces 5.2 Inner product spaces

Inner Product Spaces 5.2 Inner product spaces Inner Product Spaces 5.2 Inner product spaces November 15 Goals Concept of length, distance, and angle in R 2 or R n is extended to abstract vector spaces V. Sucn a vector space will be called an Inner

More information

12.5 Equations of Lines and Planes

12.5 Equations of Lines and Planes 12.5 Equations of Lines and Planes Equation of Lines Vector Equation of Lines Parametric Equation of Lines Symmetric Equation of Lines Relation Between Two Lines Equations of Planes Vector Equation of

More information

The Cross Product. In this section, we will learn about: Cross products of vectors and their applications.

The Cross Product. In this section, we will learn about: Cross products of vectors and their applications. The Cross Product In this section, we will learn about: Cross products of vectors and their applications. THE CROSS PRODUCT The cross product a x b of two vectors a and b, unlike the dot product, is a

More information

45. The Parallelogram Law states that. product of a and b is the vector a b a 2 b 3 a 3 b 2, a 3 b 1 a 1 b 3, a 1 b 2 a 2 b 1. a c. a 1. b 1.

45. The Parallelogram Law states that. product of a and b is the vector a b a 2 b 3 a 3 b 2, a 3 b 1 a 1 b 3, a 1 b 2 a 2 b 1. a c. a 1. b 1. SECTION 10.4 THE CROSS PRODUCT 537 42. Suppose that all sides of a quadrilateral are equal in length and opposite sides are parallel. Use vector methods to show that the diagonals are perpendicular. 43.

More information

Math 1600B Lecture 4, Section 2, 13 Jan 2014

Math 1600B Lecture 4, Section 2, 13 Jan 2014 1 of 8 Math 1600B Lecture 4, Section 2, 13 Jan 2014 Announcements: Read Section 13 for next class Work through recommended homework questions Tutorials start this week, and include a quiz covering Sections

More information

Designing Information Devices and Systems I Fall 2018 Lecture Notes Note 21

Designing Information Devices and Systems I Fall 2018 Lecture Notes Note 21 EECS 16A Designing Information Devices and Systems I Fall 2018 Lecture Notes Note 21 21.1 Module Goals In this module, we introduce a family of ideas that are connected to optimization and machine learning,

More information

Dot product. The dot product is an inner product on a coordinate vector space (Definition 1, Theorem

Dot product. The dot product is an inner product on a coordinate vector space (Definition 1, Theorem Dot product The dot product is an inner product on a coordinate vector space (Definition 1, Theorem 1). Definition 1 Given vectors v and u in n-dimensional space, the dot product is defined as, n v u v

More information

4.3 - Linear Combinations and Independence of Vectors

4.3 - Linear Combinations and Independence of Vectors - Linear Combinations and Independence of Vectors De nitions, Theorems, and Examples De nition 1 A vector v in a vector space V is called a linear combination of the vectors u 1, u,,u k in V if v can be

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

Skill: determine an approximate value of a radical expression using a variety of methods.

Skill: determine an approximate value of a radical expression using a variety of methods. Skill: determine an approximate value of a radical expression using a variety of methods. N.RN.A. Extend the properties of exponents to rational exponents. Rewrite expressions involving radicals and rational

More information

Extra Problems for Math 2050 Linear Algebra I

Extra Problems for Math 2050 Linear Algebra I Extra Problems for Math 5 Linear Algebra I Find the vector AB and illustrate with a picture if A = (,) and B = (,4) Find B, given A = (,4) and [ AB = A = (,4) and [ AB = 8 If possible, express x = 7 as

More information

58. The Triangle Inequality for vectors is. dot product.] 59. The Parallelogram Law states that

58. The Triangle Inequality for vectors is. dot product.] 59. The Parallelogram Law states that 786 CAPTER 12 VECTORS AND TE GEOETRY OF SPACE 0, 0, 1, and 1, 1, 1 as shown in the figure. Then the centroid is. ( 1 2, 1 2, 1 2 ) ] x z C 54. If c a a, where a,, and c are all nonzero vectors, show that

More information

Quantities which have only magnitude are called scalars. Quantities which have magnitude and direction are called vectors.

Quantities which have only magnitude are called scalars. Quantities which have magnitude and direction are called vectors. Vectors summary Quantities which have only magnitude are called scalars. Quantities which have magnitude and direction are called vectors. AB is the position vector of B relative to A and is the vector

More information

which has a check digit of 9. This is consistent with the first nine digits of the ISBN, since

which has a check digit of 9. This is consistent with the first nine digits of the ISBN, since vector Then the check digit c is computed using the following procedure: 1. Form the dot product. 2. Divide by 11, thereby producing a remainder c that is an integer between 0 and 10, inclusive. The check

More information

Give a geometric description of the set of points in space whose coordinates satisfy the given pair of equations.

Give a geometric description of the set of points in space whose coordinates satisfy the given pair of equations. 1. Give a geometric description of the set of points in space whose coordinates satisfy the given pair of equations. x + y = 5, z = 4 Choose the correct description. A. The circle with center (0,0, 4)

More information

Section 13.4 The Cross Product

Section 13.4 The Cross Product Section 13.4 The Cross Product Multiplying Vectors 2 In this section we consider the more technical multiplication which can be defined on vectors in 3-space (but not vectors in 2-space). 1. Basic Definitions

More information

10.2,3,4. Vectors in 3D, Dot products and Cross Products

10.2,3,4. Vectors in 3D, Dot products and Cross Products Name: Section: 10.2,3,4. Vectors in 3D, Dot products and Cross Products 1. Sketch the plane parallel to the xy-plane through (2, 4, 2) 2. For the given vectors u and v, evaluate the following expressions.

More information

HOMEWORK PROBLEMS FROM STRANG S LINEAR ALGEBRA AND ITS APPLICATIONS (4TH EDITION)

HOMEWORK PROBLEMS FROM STRANG S LINEAR ALGEBRA AND ITS APPLICATIONS (4TH EDITION) HOMEWORK PROBLEMS FROM STRANG S LINEAR ALGEBRA AND ITS APPLICATIONS (4TH EDITION) PROFESSOR STEVEN MILLER: BROWN UNIVERSITY: SPRING 2007 1. CHAPTER 1: MATRICES AND GAUSSIAN ELIMINATION Page 9, # 3: Describe

More information

94 CHAPTER 3. VECTORS AND THE GEOMETRY OF SPACE

94 CHAPTER 3. VECTORS AND THE GEOMETRY OF SPACE 94 CHAPTER 3. VECTORS AND THE GEOMETRY OF SPACE 3.3 Dot Product We haven t yet de ned a multiplication between vectors. It turns out there are di erent ways this can be done. In this section, we present

More information

Vectors. 1 Basic Definitions. Liming Pang

Vectors. 1 Basic Definitions. Liming Pang Vectors Liming Pang 1 Basic Definitions Definition 1. A vector in a line/plane/space is a quantity which has both magnitude and direction. The magnitude is a nonnegative real number and the direction is

More information

Big Ideas: determine an approximate value of a radical expression using a variety of methods. REVIEW Radicals

Big Ideas: determine an approximate value of a radical expression using a variety of methods. REVIEW Radicals Big Ideas: determine an approximate value of a radical expression using a variety of methods. REVIEW N.RN. Rewrite expressions involving radicals and rational exponents using the properties of exponents.

More information

Definitions and Properties of R N

Definitions and Properties of R N Definitions and Properties of R N R N as a set As a set R n is simply the set of all ordered n-tuples (x 1,, x N ), called vectors. We usually denote the vector (x 1,, x N ), (y 1,, y N ), by x, y, or

More information

INNER PRODUCT SPACE. Definition 1

INNER PRODUCT SPACE. Definition 1 INNER PRODUCT SPACE Definition 1 Suppose u, v and w are all vectors in vector space V and c is any scalar. An inner product space on the vectors space V is a function that associates with each pair of

More information

Inner products. Theorem (basic properties): Given vectors u, v, w in an inner product space V, and a scalar k, the following properties hold:

Inner products. Theorem (basic properties): Given vectors u, v, w in an inner product space V, and a scalar k, the following properties hold: Inner products Definition: An inner product on a real vector space V is an operation (function) that assigns to each pair of vectors ( u, v) in V a scalar u, v satisfying the following axioms: 1. u, v

More information

Vectors. The standard geometric definition of vector is as something which has direction and magnitude but not position.

Vectors. The standard geometric definition of vector is as something which has direction and magnitude but not position. Vectors The standard geometric definition of vector is as something which has direction and magnitude but not position. Since vectors have no position we may place them wherever is convenient. Vectors

More information

Vector Geometry. Chapter 5

Vector Geometry. Chapter 5 Chapter 5 Vector Geometry In this chapter we will look more closely at certain geometric aspects of vectors in R n. We will first develop an intuitive understanding of some basic concepts by looking at

More information

Order of Operations. Real numbers

Order of Operations. Real numbers Order of Operations When simplifying algebraic expressions we use the following order: 1. Perform operations within a parenthesis. 2. Evaluate exponents. 3. Multiply and divide from left to right. 4. Add

More information

A summary of factoring methods

A summary of factoring methods Roberto s Notes on Prerequisites for Calculus Chapter 1: Algebra Section 1 A summary of factoring methods What you need to know already: Basic algebra notation and facts. What you can learn here: What

More information

Linear Algebra Massoud Malek

Linear Algebra Massoud Malek CSUEB Linear Algebra Massoud Malek Inner Product and Normed Space In all that follows, the n n identity matrix is denoted by I n, the n n zero matrix by Z n, and the zero vector by θ n An inner product

More information

Algebra 1 (cp) Midterm Review Name: Date: Period:

Algebra 1 (cp) Midterm Review Name: Date: Period: Algebra 1 (cp) Midterm Review Name: Date: Period: Chapter 1 1. Evaluate the variable expression when j 4. j 44 [1] 2. Evaluate the variable expression when j 4. 24 j [2] 3. Find the perimeter of the rectangle.

More information

Practical Linear Algebra: A Geometry Toolbox

Practical Linear Algebra: A Geometry Toolbox Practical Linear Algebra: A Geometry Toolbox Third edition Chapter 2: Here and There: Points and Vectors in 2D Gerald Farin & Dianne Hansford CRC Press, Taylor & Francis Group, An A K Peters Book www.farinhansford.com/books/pla

More information

NAME: Mathematics 133, Fall 2013, Examination 3

NAME: Mathematics 133, Fall 2013, Examination 3 NAME: Mathematics 133, Fall 2013, Examination 3 INSTRUCTIONS: Work all questions, and unless indicated otherwise give reasons for your answers. If the problem does not explicitly state that the underlying

More information

SOLUTIONS TO EXERCISES FOR MATHEMATICS 133 Part 1. I. Topics from linear algebra

SOLUTIONS TO EXERCISES FOR MATHEMATICS 133 Part 1. I. Topics from linear algebra SOLUTIONS TO EXERCISES FOR MATHEMATICS 133 Part 1 Winter 2009 I. Topics from linear algebra I.0 : Background 1. Suppose that {x, y} is linearly dependent. Then there are scalars a, b which are not both

More information

12.1 Three Dimensional Coordinate Systems (Review) Equation of a sphere

12.1 Three Dimensional Coordinate Systems (Review) Equation of a sphere 12.2 Vectors 12.1 Three Dimensional Coordinate Systems (Reiew) Equation of a sphere x a 2 + y b 2 + (z c) 2 = r 2 Center (a,b,c) radius r 12.2 Vectors Quantities like displacement, elocity, and force inole

More information

Calculus III (MAC )

Calculus III (MAC ) Calculus III (MAC2-) Test (25/9/7) Name (PRINT): Please show your work. An answer with no work receives no credit. You may use the back of a page if you need more space for a problem. You may not use any

More information

MATH CSE20 Homework 5 Due Monday November 4

MATH CSE20 Homework 5 Due Monday November 4 MATH CSE20 Homework 5 Due Monday November 4 Assigned reading: NT Section 1 (1) Prove the statement if true, otherwise find a counterexample. (a) For all natural numbers x and y, x + y is odd if one of

More information

15. LECTURE 15. I can calculate the dot product of two vectors and interpret its meaning. I can find the projection of one vector onto another one.

15. LECTURE 15. I can calculate the dot product of two vectors and interpret its meaning. I can find the projection of one vector onto another one. 5. LECTURE 5 Objectives I can calculate the dot product of two vectors and interpret its meaning. I can find the projection of one vector onto another one. In the last few lectures, we ve learned that

More information

Math 11 Fall 2018 Practice Final Exam

Math 11 Fall 2018 Practice Final Exam Math 11 Fall 218 Practice Final Exam Disclaimer: This practice exam should give you an idea of the sort of questions we may ask on the actual exam. Since the practice exam (like the real exam) is not long

More information

LINEAR ALGEBRA W W L CHEN

LINEAR ALGEBRA W W L CHEN LINEAR ALGEBRA W W L CHEN c W W L Chen, 1997, 2008. This chapter is available free to all individuals, on the understanding that it is not to be used for financial gain, and may be downloaded and/or photocopied,

More information

10.1 Vectors. c Kun Wang. Math 150, Fall 2017

10.1 Vectors. c Kun Wang. Math 150, Fall 2017 10.1 Vectors Definition. A vector is a quantity that has both magnitude and direction. A vector is often represented graphically as an arrow where the direction is the direction of the arrow, and the magnitude

More information

Chapter 12 Review Vector. MATH 126 (Section 9.5) Vector and Scalar The University of Kansas 1 / 30

Chapter 12 Review Vector. MATH 126 (Section 9.5) Vector and Scalar The University of Kansas 1 / 30 Chapter 12 Review Vector MATH 126 (Section 9.5) Vector and Scalar The University of Kansas 1 / 30 iclicker 1: Let v = PQ where P = ( 2, 5) and Q = (1, 2). Which of the following vectors with the given

More information

MATH 19520/51 Class 2

MATH 19520/51 Class 2 MATH 19520/51 Class 2 Minh-Tam Trinh University of Chicago 2017-09-27 1 Review dot product. 2 Angles between vectors and orthogonality. 3 Projection of one vector onto another. 4 Cross product and its

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

There are two things that are particularly nice about the first basis

There are two things that are particularly nice about the first basis Orthogonality and the Gram-Schmidt Process In Chapter 4, we spent a great deal of time studying the problem of finding a basis for a vector space We know that a basis for a vector space can potentially

More information

Study guide for Exam 1. by William H. Meeks III October 26, 2012

Study guide for Exam 1. by William H. Meeks III October 26, 2012 Study guide for Exam 1. by William H. Meeks III October 2, 2012 1 Basics. First we cover the basic definitions and then we go over related problems. Note that the material for the actual midterm may include

More information

Review of Coordinate Systems

Review of Coordinate Systems Vector in 2 R and 3 R Review of Coordinate Systems Used to describe the position of a point in space Common coordinate systems are: Cartesian Polar Cartesian Coordinate System Also called rectangular coordinate

More information

Math 302 Test 1 Review

Math 302 Test 1 Review Math Test Review. Given two points in R, x, y, z and x, y, z, show the point x + x, y + y, z + z is on the line between these two points and is the same distance from each of them. The line is rt x, y,

More information

right angle an angle whose measure is exactly 90ᴼ

right angle an angle whose measure is exactly 90ᴼ right angle an angle whose measure is exactly 90ᴼ m B = 90ᴼ B two angles that share a common ray A D C B Vertical Angles A D C B E two angles that are opposite of each other and share a common vertex two

More information

The Dot Product

The Dot Product The Dot Product 1-9-017 If = ( 1,, 3 ) and = ( 1,, 3 ) are ectors, the dot product of and is defined algebraically as = 1 1 + + 3 3. Example. (a) Compute the dot product (,3, 7) ( 3,,0). (b) Compute the

More information

Name These exercises cover topics from Algebra I and Algebra II. Complete each question the best you can.

Name These exercises cover topics from Algebra I and Algebra II. Complete each question the best you can. Name These eercises cover topics from Algebra I and Algebra II. Complete each question the best you can. Multiple Choice: Place through the letter of the correct answer. You may only use your calculator

More information

Math 276, Spring 2007 Additional Notes on Vectors

Math 276, Spring 2007 Additional Notes on Vectors Math 276, Spring 2007 Additional Notes on Vectors 1.1. Real Vectors. 1. Scalar Products If x = (x 1,..., x n ) is a vector in R n then the length of x is x = x 2 1 + + x2 n. We sometimes use the notation

More information

Day 2 and 3 Graphing Linear Inequalities in Two Variables.notebook. Formative Quiz. 1) Sketch the graph of the following linear equation.

Day 2 and 3 Graphing Linear Inequalities in Two Variables.notebook. Formative Quiz. 1) Sketch the graph of the following linear equation. Formative Quiz 1) Sketch the graph of the following linear equation. (a) 1 (b) 2 2. Solve for x in the given triangle. 12 53 0 x 47 0 3 3. Solve for x in the given triangle. 87 0 13 9 x 4 5 Graphing Linear

More information

Chapter 1. Preliminaries

Chapter 1. Preliminaries Chapter 1 Preliminaries 1.1 The Vector Concept Revisited The concept of a vector has been one of the most fruitful ideas in all of mathematics, and it is not surprising that we receive repeated exposure

More information

OHSx XM521 Multivariable Differential Calculus: Homework Solutions 13.1

OHSx XM521 Multivariable Differential Calculus: Homework Solutions 13.1 OHSx XM521 Multivariable Differential Calculus: Homework Solutions 13.1 (37) If a bug walks on the sphere x 2 + y 2 + z 2 + 2x 2y 4z 3 = 0 how close and how far can it get from the origin? Solution: Complete

More information

(, ) : R n R n R. 1. It is bilinear, meaning it s linear in each argument: that is

(, ) : R n R n R. 1. It is bilinear, meaning it s linear in each argument: that is 17 Inner products Up until now, we have only examined the properties of vectors and matrices in R n. But normally, when we think of R n, we re really thinking of n-dimensional Euclidean space - that is,

More information

web: HOMEWORK 1

web:   HOMEWORK 1 MAT 207 LINEAR ALGEBRA I 2009207 Dokuz Eylül University, Faculty of Science, Department of Mathematics Instructor: Engin Mermut web: http://kisideuedutr/enginmermut/ HOMEWORK VECTORS IN THE n-dimensional

More information

Answers in blue. If you have questions or spot an error, let me know. 1. Find all matrices that commute with A =. 4 3

Answers in blue. If you have questions or spot an error, let me know. 1. Find all matrices that commute with A =. 4 3 Answers in blue. If you have questions or spot an error, let me know. 3 4. Find all matrices that commute with A =. 4 3 a b If we set B = and set AB = BA, we see that 3a + 4b = 3a 4c, 4a + 3b = 3b 4d,

More information

Lecture Note on Linear Algebra 17. Standard Inner Product

Lecture Note on Linear Algebra 17. Standard Inner Product Lecture Note on Linear Algebra 17. Standard Inner Product Wei-Shi Zheng, wszheng@ieee.org, 2011 November 21, 2011 1 What Do You Learn from This Note Up to this point, the theory we have established can

More information

MAT 419 Lecture Notes Transcribed by Eowyn Cenek 6/1/2012

MAT 419 Lecture Notes Transcribed by Eowyn Cenek 6/1/2012 (Homework 1: Chapter 1: Exercises 1-7, 9, 11, 19, due Monday June 11th See also the course website for lectures, assignments, etc) Note: today s lecture is primarily about definitions Lots of definitions

More information

Linear Equations. Find the domain and the range of the following set. {(4,5), (7,8), (-1,3), (3,3), (2,-3)}

Linear Equations. Find the domain and the range of the following set. {(4,5), (7,8), (-1,3), (3,3), (2,-3)} Linear Equations Domain and Range Domain refers to the set of possible values of the x-component of a point in the form (x,y). Range refers to the set of possible values of the y-component of a point in

More information

Vector equations of lines in the plane and 3-space (uses vector addition & scalar multiplication).

Vector equations of lines in the plane and 3-space (uses vector addition & scalar multiplication). Boise State Math 275 (Ultman) Worksheet 1.6: Lines and Planes From the Toolbox (what you need from previous classes) Plotting points, sketching vectors. Be able to find the component form a vector given

More information

4.1 Distance and Length

4.1 Distance and Length Chapter Vector Geometry In this chapter we will look more closely at certain geometric aspects of vectors in R n. We will first develop an intuitive understanding of some basic concepts by looking at vectors

More information

1 Review of the dot product

1 Review of the dot product Any typographical or other corrections about these notes are welcome. Review of the dot product The dot product on R n is an operation that takes two vectors and returns a number. It is defined by n u

More information

Vectors, dot product, and cross product

Vectors, dot product, and cross product MTH 201 Multivariable calculus and differential equations Practice problems Vectors, dot product, and cross product 1. Find the component form and length of vector P Q with the following initial point

More information

Solutions to assignment 5. x y = x z + z y x z + z y < = 5. x y x z = x (y z) x y z x y + ( z) x ( y + z ) < 2 (3 + 4) = 14,

Solutions to assignment 5. x y = x z + z y x z + z y < = 5. x y x z = x (y z) x y z x y + ( z) x ( y + z ) < 2 (3 + 4) = 14, Solutions to assignment 5 8..: a) x y = x z + z y x z + z y < 2 + 3 = 5 b) x y x z = x (y z) x y z x y + ( z) x ( y + z ) < 2 (3 + 4) = 4, where I used the Cauchy-Schwartz inequality in the first step,

More information

Maths A Level Summer Assignment & Transition Work

Maths A Level Summer Assignment & Transition Work Maths A Level Summer Assignment & Transition Work The summer assignment element should take no longer than hours to complete. Your summer assignment for each course must be submitted in the relevant first

More information

M17 MAT25-21 HOMEWORK 6

M17 MAT25-21 HOMEWORK 6 M17 MAT25-21 HOMEWORK 6 DUE 10:00AM WEDNESDAY SEPTEMBER 13TH 1. To Hand In Double Series. The exercises in this section will guide you to complete the proof of the following theorem: Theorem 1: Absolute

More information

v = ( 2)

v = ( 2) Chapter : Introduction to Vectors.. Vectors and linear combinations Let s begin by saying what vectors are: They are lists of numbers. If there are numbers in the list, there is a natural correspondence

More information

Class IX Chapter 5 Introduction to Euclid's Geometry Maths

Class IX Chapter 5 Introduction to Euclid's Geometry Maths Class IX Chapter 5 Introduction to Euclid's Geometry Maths Exercise 5.1 Question 1: Which of the following statements are true and which are false? Give reasons for your answers. (i) Only one line can

More information

a. Define a function called an inner product on pairs of points x = (x 1, x 2,..., x n ) and y = (y 1, y 2,..., y n ) in R n by

a. Define a function called an inner product on pairs of points x = (x 1, x 2,..., x n ) and y = (y 1, y 2,..., y n ) in R n by Real Analysis Homework 1 Solutions 1. Show that R n with the usual euclidean distance is a metric space. Items a-c will guide you through the proof. a. Define a function called an inner product on pairs

More information

Notes on multivariable calculus

Notes on multivariable calculus Notes on multivariable calculus Jonathan Wise February 2, 2010 1 Review of trigonometry Trigonometry is essentially the study of the relationship between polar coordinates and Cartesian coordinates in

More information

MATH 12 CLASS 2 NOTES, SEP Contents. 2. Dot product: determining the angle between two vectors 2

MATH 12 CLASS 2 NOTES, SEP Contents. 2. Dot product: determining the angle between two vectors 2 MATH 12 CLASS 2 NOTES, SEP 23 2011 Contents 1. Dot product: definition, basic properties 1 2. Dot product: determining the angle between two vectors 2 Quick links to definitions/theorems Dot product definition

More information

HOMEWORK 1: SOLUTIONS - MATH 215 INSTRUCTOR: George Voutsadakis

HOMEWORK 1: SOLUTIONS - MATH 215 INSTRUCTOR: George Voutsadakis HOMEWORK 1: SOLUTIONS - MATH 215 INSTRUCTOR: George Voutsadakis Problem 1 Make truth tables for the propositional forms (P Q) (P R) and (P Q) (R S). Solution: P Q R P Q P R (P Q) (P R) F F F F F F F F

More information

Rigid Geometric Transformations

Rigid Geometric Transformations Rigid Geometric Transformations Carlo Tomasi This note is a quick refresher of the geometry of rigid transformations in three-dimensional space, expressed in Cartesian coordinates. 1 Cartesian Coordinates

More information

SOLUTIONS TO ADDITIONAL EXERCISES FOR II.1 AND II.2

SOLUTIONS TO ADDITIONAL EXERCISES FOR II.1 AND II.2 SOLUTIONS TO ADDITIONAL EXERCISES FOR II.1 AND II.2 Here are the solutions to the additional exercises in betsepexercises.pdf. B1. Let y and z be distinct points of L; we claim that x, y and z are not

More information