Vectors in Space. Standard Graphing

Size: px
Start display at page:

Download "Vectors in Space. Standard Graphing"

Transcription

1 Vectors in Space O restart:with(plots);with(vectorcalculus): animate, animated, animatecurve, arrow, changecoords, complexplot, complexplotd, conformal, conformald, contourplot, contourplotd, coordplot, coordplotd, densitplot, displa, dualaxisplot, fieldplot, fieldplotd, gradplot, gradplotd, graphplotd, implicitplot, implicitplotd, inequal, interactive, interactiveparams, intersectplot, listcontplot, listcontplotd, listdensitplot, listplot, listplotd, loglogplot, logplot, matrixplot, multiple, odeplot, pareto, plotcompare, pointplot, pointplotd, polarplot, polgonplot, polgonplotd, polhedra_supported, polhedraplot, rootlocus, semilogplot, setcolors, setoptions, setoptionsd, spacecurve, sparsematrixplot, surfdata, textplot, textplotd, tubeplot Standard Graphing To displa the NORMAL coordinate axes, let's graph the points (,,) and (,,6), and join them with a line. O p:=pointplotd({[,,],[,,6]},axes=normal,labels=[x,,], connect=true,color=blue,thickness=): p:=textplotd([,,,"(,,6)",font=[times,bold,],color= magenta]): displa(p,p);

2 6.. x.. (,,6). We can also view our graph within a box, using the option "axes=boxed." O p:=pointplotd({[,,],[,,6]},axes=boxed,labels=[x,,], connect=true,color=blue,thickness=): p:=textplotd([.,,,"(,,6)",font=[times,bold,],color= magenta]): displa(p,p);

3 6 (,,6).... x. The perspective seems all wrong in both cases. It is the default orientation [, ]=[, ]. Let's tr an alternate orientation of [, ]=[,7]. O p:=pointplotd({[,,],[,,6]},axes=normal,labels=[x,,], connect=true,color=blue,thickness=,orientation=[,7]): O p:=plotd([*s,*s,],s=..,t=..,axes=normal,labels=[x,,], thickness=,orientation=[,7]): O p:=plotd([*s,*s,6],s=..,t=..,axes=normal,labels=[x,,], thickness=,orientation=[,7]): O p:=plotd([,,s],s=..6,t=..,axes=normal,labels=[x,,], thickness=,orientation=[,7]): p:=textplotd([,,7,"(,,6)",font=[times,bold,],color= magenta]): O displa(p,p,p,p,p);

4 7 6 (,,6).. x... This is better. An orientation of [, ]=[,] has the positive axis pointing out perpendicularl from the screen, the positive x axis pointing downward, and the positive axis pointing to the right. A of moves the x- plane degrees clockwise, and a of 7 tilts the positive -axis so that it makes an angle of (9-7) degrees with the screen. We will use the setoptionsd command to set d graphing options that we want for all d graphs until Maple is restarted. These no longer need to be explicitl stated as the were above. O setoptionsd(axes=normal,labels=[x,,],orientation=[,7]); We see we now get the same graph as above without needing to tpe in so man options. O p:=pointplotd({[,,],[,,6]},connect=true,color=blue, thickness=): O p:=plotd([*s,*s,],s=..,t=..,thickness=): O p:=plotd([*s,*s,6],s=..,t=..,thickness=): O p:=plotd([,,s],s=..6,t=..,thickness=): p:=textplotd([,,7,"(,,6)",font=[times,bold,],color= magenta]): O displa(p,p,p,p,p);

5 7 6 (,,6).. x... Some people prefer a boxed axis sstem. Let's look at the above graph with boxed axes. O p:=pointplotd({[,,],[,,6]},connect=true,color=blue, thickness=): O p:=plotd([*s,*s,],s=..,t=..,thickness=): O p:=plotd([*s,*s,6],s=..,t=..,thickness=): O p:=plotd([,,s],s=..6,t=..,thickness=): p:=textplotd([,,7,"(,,6)",font=[times,bold,],color= magenta]): O displa(p,p,p,p,p,axes=boxed);

6 7 6 (,,6)... x.. Notice how the default axes option was overridden b the option "axes=boxed" in the displa command. Another stle that can be used is a framed axis sstem. O p:=pointplotd({[,,],[,,6]},connect=true,color=blue, thickness=): O p:=plotd([*s,*s,],s=..,t=..,thickness=): O p:=plotd([*s,*s,6],s=..,t=..,thickness=): O p:=plotd([,,s],s=..6,t=..,thickness=): p:=textplotd([,,7,"(,,6)",font=[times,bold,],color= magenta]): O displa(p,p,p,p,p,axes=framed); 6

7 7 6 (,,6)... x.. Now let's follow the coordinates to reach our point [,,6]. Starting at the origin, we fisrt move a distance of in the positive x direction. O p:=pointplotd({[,,],[,,6]},connect=true,color=blue, thickness=): O p:=plotd([*s,,],s=..,t=..,thickness=): p:=textplotd([,.,,"(,,)",font=[times,bold,],color= magenta]): O displa(p,p,p); 7

8 6.. x... (,,) Then we move in the positive direction. O p:=pointplotd({[,,],[,,6]},connect=true,color=blue, thickness=): O p:=plotd([*s,,],s=..,t=..,thickness=): O p:=plotd([,*s,],s=..,t=..,thickness=): p:=textplotd([,.,,"(,,)",font=[times,bold,],color= magenta]): O displa(p,p,p,p); 8

9 6.. x... (,,) Finall, we move 6 in the positive direction. O p:=pointplotd({[,,],[,,6]},connect=true,color=blue, thickness=): O p:=plotd([*s,,],s=..,t=..,thickness=): O p:=plotd([,*s,],s=..,t=..,thickness=): O p:=plotd([,,s],s=..6,t=..,thickness=): p:=textplotd([,,7,"(,,6)",font=[times,bold,],color= magenta]): O displa(p,p,p,p,p); 9

10 7 6 (,,6).. x... Next, we look at the graphs of the three planes =, = K, and =. Note that, for instance, the equation = means x C C = in this -dimensional context. Also, notice that the graph of = is the x- plane. O plotd({-,,},x=-..,=-..);

11 -. x We can see the axes better b removing the grid, using the option "stle=patchnogrid" (instead of the default PATCH). O plotd({-,,},x=-..,=-..,stle=patchnogrid);

12 -. x We can even extend the vertical axis if we wish, using the view option to set the extent of the -axis. O p:=plotd({-,,},x=-..,=-..,view=-6..6,stle= PATCHNOGRID): p:=textplotd([,,,"x- plane",font=[times,bold,],color= magenta]): displa(p,p);

13 x x- plane Next, let's graph the x- plane using parametric plotting and using the view option to set a viewing window and "scaling = CONSTRAINED" to have equal scales on each axis. O p:=plotd([x,,],x=-6..6,=-6..6,view=[-6..6,-6..6,-6..6], stle=patchnogrid,scaling=constrained): p:=textplotd([,,,"x- plane",font=[times,bold,],color= magenta]): displa(p,p);

14 x x- plane. -6. Finall, we graph the - plane. O p:=plotd([,,],=-6..6,=-6..6,view=[-6..6,-6..6,-6..6], stle=patchnogrid,scaling=constrained): p:=textplotd([,.,,"- plane",font=[times,bold,],color= magenta]): displa(p,p);

15 plane -6. x Defining free vectors (arrows), rooted vectors, and position vectors in dimensions. So that we can enter vectors using standard vector notation, we set BasisFormat to false. O BasisFormat(false): We can enter free vectors as either column (the default) or row vectors. There are two was to enter column vectors. O v:=<,-,7>; v := K 7 O v:=vector([,-,]); v := K We enter row vectors as follows. O v:=< 7>;

16 v := 7 We use the About statement to gain information about these vectors. O About(v);About(v);About(v); Tpe: Free Vector Components:, K, 7 Coordinates: cartesian Tpe: Free Vector Components:, K, Coordinates: cartesian Tpe: Free Vector Components:,, 7 Coordinates: cartesian Free vectors are plotted using PlotVector the command. O p:=plotvector(v,view=[-..,-..,-7..7]): p:=textplotd([,-,,"<,-,7>",font=[times,bold,],color= green]): displa(p,p); 6

17 . <,-,7> x We can adjust the shape of the arrow b using parameters. O p:=plotvector(v,view=[-..,-..,-7..7],width=.,head_width=.,head_length=.,color=blue): p:=textplotd([,-,6,"<,-,7>",font=[times,bold,],color= green]): displa(p,p); 7

18 <,-,7> x If head_length is not given, the head is about the length of the arrow. O p:=plotvector(v,view=[-..,-..,-7..7],width=.,head_width=.,color=can): p:=textplotd([,-,7,"<,-,7>",font=[times,bold,],color= green]): displa(p,p); 8

19 <,-,7> x A rooted vector is an arrow whose tail is fixed to a point in the plane. For instance, place the tail of v at the point (-,-,). O p:=plotvector(<,-,>,v,view=[-..,-..8,-..],width=.,head_width=.,head_length=.,color=green): p:=textplotd([,-8,7,"<,-,7>",font=[times,bold,],color= green]): displa(p,p); 9

20 . 9. <,-,7> x We define and plot a rooted vector using RootedVector as follows. O v:=rootedvector(root=[-,-,-],[,,7]); v := 7 O O About(v); Tpe: Rooted Vector Components:,, 7 Coordinates: cartesian Root Point: K, K, K p:=plotvector(v,view=[-8..8,-..,-..],width=.,head_width=.,head_length=.,color=orange): p:=textplotd([,-,,"<,,7>",font=[times,bold,],color= green]): displa(p,p);

21 <,,7>.. x We define and plot a position vector, a vector with tail at the origin, using PositionVector as follows. O v:=positionvector([,-,]); O O About(v); v := K Tpe: Position Vector Components:, K, Coordinates: cartesian Root Point:,, p:=plotvector(v,view=[-..,-..,-..6],width=.,head_width=.,head_length=.,color=violet): p:=textplotd([,-.,,"<,-,>",font=[times,bold,],color= green]): displa(p,p);

22 . <,-,>.. x Basic Operations for Vectors. O restart:with(plots):with(vectorcalculus):basisformat(false): O setoptionsd(axes=normal,labels=[x,,],orientation=[,7]); We first define six (column) vectors: two free, two rooted, and two position. O v:=<,,>;v:=<-6,,->;v:=rootedvector(root=[-,,],[-,, ]);v:=rootedvector(root=[-,,],[,,-]);v:=positionvector( [,,]);v6:=positionvector([-,,-]); v := v := K6 K

23 v := v := v := v6 := K K K K We use the Norm command to find the norm or magnitude of the six vectors. Since there are several vector norms, with the VectorCalculus package defaulting to the Euclidean (or ) norm and the LinearAlgebra package defaulting the the infinit (or N) norm, we will write Norm(v,) to find the Euclidean norm of a vector v in the usual cases, and use Norm(v,infinit) if we ever want the infinit norm. O Norm(v,);Norm(v,);Norm(v,);Norm(v,);Norm(v,);Norm(v6, ); 8 Vector addition is done b component. We first add two free vectors and then two position vectors. O v:=v+v;about(v);v6:=v+v6;about(v6); K v := 7 K Tpe: Components: Coordinates: Free Vector K, 7, K cartesian

24 v6 := K Tpe: Position Vector Components:,, K Coordinates: cartesian Root Point:,, We see the sums are of the same tpe as the addends. Rooted vectors can onl be added if their roots (points of origin) are the same with the sum having the same root. O v:=v+v;about(v); v := Tpe: Rooted Vector Components:,, Coordinates: cartesian Root Point: K,, What about adding a free or position vector to a rooted vector? O v:=v+v;about(v); K v := 7 O v:=v+v;about(v); Tpe: Rooted Vector Components: K, 7, Coordinates: cartesian Root Point: K,, v := 6 Tpe: Rooted Vector Components:,, 6 Coordinates: cartesian Root Point: K,,

25 We see the sum is a rooted vector with the same root as the rooted addend. What about a free vector with a position vector? O v:=v+v;about(v); 8 v := 6 Tpe: Free Vector Components: 8, 6, Coordinates: cartesian The sum is a free vector. We now wish to visualie vector addition. We must first add the LinearAlgebra subpackage of the Student package. O with(student[linearalgebra]): O p:=vectorsumplot(v,v): p:=textplotd({[,,,"v"],[,,,"v"],[,6,7,"v"],[,6,, "v"],[,9,6,"v=v+v"]},font=[times,bold,],color=black): displa(p,p); The Sum of Vectors.8 v v=v+v.8 v.8 -. x -. v v 6 8 We can see addition b the parallelogram law and the tip-to-tail method are both illustrated for v+

26 v=v. We can also see that vector addition is commutative. We can also use the same diagram to indicate subtraction. O p:=vectorsumplot(v,v): p:=textplotd({[,,,"v"],[,,,"v"],[,6,7,"v=v-v"], [,7,,"v=v-v"],[,,.,"v"]},font=[TIMES,BOLD,],color= black): displa(p,p); The Sum of Vectors v=v-v.8.8 v v.8 -. x.8-. v=v-v v.8.8 The upper triangle illustrates v=v-v, while the lower triangle illustrates v=v-v. We next look at scalar multiplication. We first multipl b. O w:=(/)*v;w:=(/)*v;w:=(/)*v; w := 6

27 w := w := K We view the original vectors in red and the scalar multiples in blue. O p:=plotvector([v,v,v],width=.,head_width=.,head_length=., scaling=constrained,color=red): p:=plotvector([w,w,w],width=.,head_width=.,head_length=., scaling=constrained,color=blue): p6:=textplotd({[,6,,"v"],[,,8,"v"],[.,,,"w"],[,,6, "w"],[,-.,,"v"],[,-,,"w"]},font=[times,bold,],color= black): displa(p,p,p6); 7

28 8 v 6 w v -6 x w w.. v Next we multipl b -. O :=(-)*v;:=(-)*v;:=(-)*v; K6 := K K := := 8 K K6 K K K6 Again we visualie the original vectors in red and the scalar multiples in blue. O p7:=plotvector([v,v,v],width=.,head_width=.,head_length=., scaling=constrained,color=red): p8:=plotvector([,,],width=.,head_width=.,head_length=., scaling=constrained,color=blue): 8

29 p9:=textplotd({[,,,"v"],[,6,9,"v"],[,-7,-,""],[,-6, -,""],[,-,,"v"],[,,-,""]},font=[times,bold,], color=black): displa(p7,p8,p9); 9. v v x v -6. Decomposition in Dimensions O restart:with(plots):with(plottools):with(vectorcalculus) :BasisFormat(false): O setoptionsd(axes=normal,labels=[x,,],orientation=[,7]); We enter the standard vectors. O i:=vector([,,]);j:=vector([,,]);k:=vector([,,]); i := j := 9

30 k := We view the decomposition <,,9> = i + j +9k in three dimensions. O p7:=plotvector([i,j,k],width=.,head_width=.,head_length=., scaling=constrained,color=blue): p8:=plotvector([*i,rootedvector(root=*i,[,,]),rootedvector (root=*i+*j,[,,9]),*i+*j+9*k],width=.,head_width=., head_length=.,scaling=constrained,color=red): p9:=textplotd({[,-.,,"i"],[,,.,"j"],[,-.,,"k"],[,-.,,"i"],[6.,,,"i+j"],[,,9.,"i+j+9k"]},font=[times, BOLD,],color=black): displa(p7,p8,p9); 7. i+j+9k. i. k j. i i+j x.

Taylor Polynomials restart;with(plots); with(student); with(numericalanalysis); with(student[numericalanalysis]);

Taylor Polynomials restart;with(plots); with(student); with(numericalanalysis); with(student[numericalanalysis]); Talor Polnomials Talor's Theorem is used etensivel in Numerical Analsis and is the basis for the development of several important techniques. We begin b restarting and loading the plots package for some

More information

Understanding Molecular Orbitals; Sigma Orbitals

Understanding Molecular Orbitals; Sigma Orbitals Universit of Connecticut DigitalCommons@UConn Chemistr Education Materials Department of Chemistr April 7 Understanding Molecular Orbitals; Sigma Orbitals Carl W. David Universit of Connecticut, Carl.David@uconn.edu

More information

Math Differential Equations Material Covering Lab 2

Math Differential Equations Material Covering Lab 2 Math 366 - Differential Equations Material Covering Lab 2 Separable Equations A separable equation is a first-orer ODE that can be written in the form y'= g x $h y This is the general metho to solve such

More information

Exploring Calculus Using a Maple Approach

Exploring Calculus Using a Maple Approach Exploring Calculus Using a Maple Approach Last Update: October, 00 Zhao Chen Janet Liou-Mark Arnavaz Taraporevala Table of Contents Preface... Chapter : Introduction to MAPLE... Objectives... Lab Activities...9

More information

Introduction to Maple MAT 3535

Introduction to Maple MAT 3535 Introduction to Maple MAT 3535 Wm C Bauldry BauldryWC Spring Semester, 2006 Wm C Bauldry (BauldryWC) Introduction to Maple MAT 3535 Spring Semester, 2006 1 / 50 Maple plot of a Lotka Volterra system in

More information

MAPLE TM LAB MANUAL FOR MATH 237

MAPLE TM LAB MANUAL FOR MATH 237 MAPLE TM LAB MANUAL FOR MATH 237 Differential Equations and Computer Methods Written by CESAR O. AGUILAR QUEEN S UNIVERSITY KINGSTON, ONTARIO, CANADA Preface This manual introduces the basic Maple tools

More information

Without a Vector Calculus Coordinate System

Without a Vector Calculus Coordinate System Classroom Tips and Techniques: Point-and-Click Access to the Differential Operators of Vector Calculus Robert J. Lopez Emeritus Professor of Mathematics and Maple Fellow Maplesoft Introduction The -operator

More information

Classroom Tips and Techniques: Electric Field from Distributed Charge

Classroom Tips and Techniques: Electric Field from Distributed Charge Classroom Tips and Techniques: Electric Field from Distributed Charge Introduction Robert J. Lopez Emeritus Professor of Mathematics and Maple Fellow Maplesoft This past summer I was asked if Maple could

More information

Lecture 11: Vector Calculus I

Lecture 11: Vector Calculus I 1. Key points Scalar and vector fields Gradient and directional derivative Laplacian Maple Derivatives VectorCalculus package SetCoordinates Vector Norm DotProduct Gradient, Del, Nabla Laplacian evalvf

More information

Review: Linear and Vector Algebra

Review: Linear and Vector Algebra Review: Linear and Vector Algebra Points in Euclidean Space Location in space Tuple of n coordinates x, y, z, etc Cannot be added or multiplied together Vectors: Arrows in Space Vectors are point changes

More information

3.1 Using Vectors 3.3 Coordinate Systems and Vector Components.notebook September 19, 2017

3.1 Using Vectors 3.3 Coordinate Systems and Vector Components.notebook September 19, 2017 Using Vectors A vector is a quantity with both a size (magnitude) and a direction. Figure 3.1 shows how to represent a particle s velocity as a vector. Section 3.1 Using Vectors The particle s speed at

More information

Vectors and Vector Arithmetic

Vectors and Vector Arithmetic Vectors and Vector Arithmetic Introduction and Goals: The purpose of this lab is to become familiar with the syntax of Maple commands for manipulating and graphing vectors. It will introduce you to basic

More information

MATH Symmetric matrices, conics and quadrics December 3, 2001

MATH Symmetric matrices, conics and quadrics December 3, 2001 MATH 70- Smmetric matrices, conics and quadrics December 3, 00 Conic sections: > restart: > with(linalg):with(plots):#for computations and pictures with(student):#to do algebra computations like completing

More information

Inner Product Spaces 6.1 Length and Dot Product in R n

Inner Product Spaces 6.1 Length and Dot Product in R n Inner Product Spaces 6.1 Length and Dot Product in R n Summer 2017 Goals We imitate the concept of length and angle between two vectors in R 2, R 3 to define the same in the n space R n. Main topics are:

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

Euclidean Spaces. Euclidean Spaces. Chapter 10 -S&B

Euclidean Spaces. Euclidean Spaces. Chapter 10 -S&B Chapter 10 -S&B The Real Line: every real number is represented by exactly one point on the line. The plane (i.e., consumption bundles): Pairs of numbers have a geometric representation Cartesian plane

More information

11.1 Vectors in the plane

11.1 Vectors in the plane 11.1 Vectors in the plane What is a vector? It is an object having direction and length. Geometric way to represent vectors It is represented by an arrow. The direction of the arrow is the direction of

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

Lesson 12: More Systems

Lesson 12: More Systems Lesson 12: More Systems restart; A geometry problem Here's a nice little application of resultants to a geometrical problem. We're given two concentric circles with radii and. From a given point P at a

More information

EXAM. Exam 1. Math 5316, Fall December 2, 2012

EXAM. Exam 1. Math 5316, Fall December 2, 2012 EXAM Exam Math 536, Fall 22 December 2, 22 Write all of your answers on separate sheets of paper. You can keep the exam questions. This is a takehome exam, to be worked individually. You can use your notes.

More information

1. Solutions to Systems of Linear Equations. Determine whether the ordered pairs are solutions to the system. x y 6. 3x y 2

1. Solutions to Systems of Linear Equations. Determine whether the ordered pairs are solutions to the system. x y 6. 3x y 2 78 Chapter Sstems of Linear Equations Section. Concepts. Solutions to Sstems of Linear Equations. Dependent and Inconsistent Sstems of Linear Equations. Solving Sstems of Linear Equations b Graphing Solving

More information

Chapter 2 - Vector Algebra

Chapter 2 - Vector Algebra A spatial vector, or simply vector, is a concept characterized by a magnitude and a direction, and which sums with other vectors according to the Parallelogram Law. A vector can be thought of as an arrow

More information

74 Maths Quest 10 for Victoria

74 Maths Quest 10 for Victoria Linear graphs Maria is working in the kitchen making some high energ biscuits using peanuts and chocolate chips. She wants to make less than g of biscuits but wants the biscuits to contain at least 8 g

More information

Phys 221. Chapter 3. Vectors A. Dzyubenko Brooks/Cole

Phys 221. Chapter 3. Vectors A. Dzyubenko Brooks/Cole Phs 221 Chapter 3 Vectors adzubenko@csub.edu http://www.csub.edu/~adzubenko 2014. Dzubenko 2014 rooks/cole 1 Coordinate Sstems Used to describe the position of a point in space Coordinate sstem consists

More information

Linear Algebra I for Science (NYC)

Linear Algebra I for Science (NYC) Element No. 1: To express concrete problems as linear equations. To solve systems of linear equations using matrices. Topic: MATRICES 1.1 Give the definition of a matrix, identify the elements and the

More information

Overview of the LinearAlgebra Package

Overview of the LinearAlgebra Package verview of the LinearAlgebra Package Basic Functionality Description The LinearAlgebra package offers routines to construct and manipulate Matrices and Vectors, compute standard operations, query results

More information

2- Scalars and Vectors

2- Scalars and Vectors 2- Scalars and Vectors Scalars : have magnitude only : Length, time, mass, speed and volume is example of scalar. v Vectors : have magnitude and direction. v The magnitude of is written v v Position, displacement,

More information

Algebra I Calculator Activities

Algebra I Calculator Activities First Nine Weeks SOL Objectives Calculating Measures of Central Tendency SOL A.17 Organize a set of data Calculate the mean, median, mode, and range of a set of data Describe the relationships between

More information

Mathematica for Calculus II (Version 9.0)

Mathematica for Calculus II (Version 9.0) Mathematica for Calculus II (Version 9.0) C. G. Melles Mathematics Department United States Naval Academy December 31, 013 Contents 1. Introduction. Volumes of revolution 3. Solving systems of equations

More information

Lecture 2: Vector-Vector Operations

Lecture 2: Vector-Vector Operations Lecture 2: Vector-Vector Operations Vector-Vector Operations Addition of two vectors Geometric representation of addition and subtraction of vectors Vectors and points Dot product of two vectors Geometric

More information

Introduction to Vectors Pg. 279 # 1 6, 8, 9, 10 OR WS 1.1 Sept. 7. Vector Addition Pg. 290 # 3, 4, 6, 7, OR WS 1.2 Sept. 8

Introduction to Vectors Pg. 279 # 1 6, 8, 9, 10 OR WS 1.1 Sept. 7. Vector Addition Pg. 290 # 3, 4, 6, 7, OR WS 1.2 Sept. 8 UNIT 1 INTRODUCTION TO VECTORS Lesson TOPIC Suggested Work Sept. 5 1.0 Review of Pre-requisite Skills Pg. 273 # 1 9 OR WS 1.0 Fill in Info sheet and get permission sheet signed. Bring in $3 for lesson

More information

Vectors Primer. M.C. Simani. July 7, 2007

Vectors Primer. M.C. Simani. July 7, 2007 Vectors Primer M.. Simani Jul 7, 2007 This note gives a short introduction to the concept of vector and summarizes the basic properties of vectors. Reference textbook: Universit Phsics, Young and Freedman,

More information

MAC Learning Objectives. Learning Objectives (Cont.) Module 10 System of Equations and Inequalities II

MAC Learning Objectives. Learning Objectives (Cont.) Module 10 System of Equations and Inequalities II MAC 1140 Module 10 System of Equations and Inequalities II Learning Objectives Upon completing this module, you should be able to 1. represent systems of linear equations with matrices. 2. transform a

More information

What are vectors. Adding Vectors

What are vectors. Adding Vectors Vectors Introduction What are vectors Each vector is defined by two pieces of information: Direction and Magnitude. Often vectors are described by a picture representation or by ordered pairs which describe

More information

Systems of Linear and Quadratic Equations. Check Skills You ll Need. y x. Solve by Graphing. Solve the following system by graphing.

Systems of Linear and Quadratic Equations. Check Skills You ll Need. y x. Solve by Graphing. Solve the following system by graphing. NY- Learning Standards for Mathematics A.A. Solve a sstem of one linear and one quadratic equation in two variables, where onl factoring is required. A.G.9 Solve sstems of linear and quadratic equations

More information

Ch 3 Alg 2 Note Sheet.doc 3.1 Graphing Systems of Equations

Ch 3 Alg 2 Note Sheet.doc 3.1 Graphing Systems of Equations Ch 3 Alg Note Sheet.doc 3.1 Graphing Sstems of Equations Sstems of Linear Equations A sstem of equations is a set of two or more equations that use the same variables. If the graph of each equation =.4

More information

Physics 12. Chapter 1: Vector Analysis in Two Dimensions

Physics 12. Chapter 1: Vector Analysis in Two Dimensions Physics 12 Chapter 1: Vector Analysis in Two Dimensions 1. Definitions When studying mechanics in Physics 11, we have realized that there are two major types of quantities that we can measure for the systems

More information

Vector and Affine Math

Vector and Affine Math Vector and Affine Math Computer Science Department The Universit of Teas at Austin Vectors A vector is a direction and a magnitude Does NOT include a point of reference Usuall thought of as an arrow in

More information

102 CHAPTER 3. VECTORS AND THE GEOMETRY OF SPACE

102 CHAPTER 3. VECTORS AND THE GEOMETRY OF SPACE 102 CHAPTER 3. VECTORS AND THE GEOMETRY OF SPACE 3.4 Cross Product 3.4.1 De nitions Unlike the dot product, the cross product is only de ned for 3-D vectors. In this section, when we use the word vector,

More information

Using Tables and Graphing Calculators in Math 11

Using Tables and Graphing Calculators in Math 11 Using Tables and Graphing Calculators in Math 11 Graphing calculators are not required for Math 11, but they are likely to be helpful, primarily because they allow you to avoid the use of tables in some

More information

Principles of Linear Algebra With Maple TM Rolling an Ellipse Along a Curve

Principles of Linear Algebra With Maple TM Rolling an Ellipse Along a Curve Principles of Linear Algebra With Maple TM Rolling an Ellipse Along a Curve Kenneth Shiskowski and Karl Frinkle c Draft date February 6, 2011 Contents 1 Rolling an Ellipse Along a Curve 1 1.1 The Setup..............................

More information

Mathematical review trigonometry vectors Motion in one dimension

Mathematical review trigonometry vectors Motion in one dimension Mathematical review trigonometry vectors Motion in one dimension Used to describe the position of a point in space Coordinate system (frame) consists of a fixed reference point called the origin specific

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

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

Analytic Geometry in Three Dimensions

Analytic Geometry in Three Dimensions Analtic Geometr in Three Dimensions. The Three-Dimensional Coordinate Sstem. Vectors in Space. The Cross Product of Two Vectors. Lines and Planes in Space The three-dimensional coordinate sstem is used

More information

CHAPTER 1 Systems of Linear Equations

CHAPTER 1 Systems of Linear Equations CHAPTER Systems of Linear Equations Section. Introduction to Systems of Linear Equations. Because the equation is in the form a x a y b, it is linear in the variables x and y. 0. Because the equation cannot

More information

Introductory Physics PHYS101

Introductory Physics PHYS101 Introductory Physics PHYS101 Dr Richard H. Cyburt Assistant Professor of Physics My office: 402c in the Science Building My phone: (304) 384-6006 My email: rcyburt@concord.edu In person or email is the

More information

Lecture 5: Vector Spaces I - Definitions

Lecture 5: Vector Spaces I - Definitions Lecture 5: Vector Spaces I - Definitions 1 Key points Many mathematical objects used in physics are elements of a Hilbert space Definition of vector spaces Definition of inner products Basis sets and expansion

More information

CHAPTER 3 : VECTORS. Definition 3.1 A vector is a quantity that has both magnitude and direction.

CHAPTER 3 : VECTORS. Definition 3.1 A vector is a quantity that has both magnitude and direction. EQT 101-Engineering Mathematics I Teaching Module CHAPTER 3 : VECTORS 3.1 Introduction Definition 3.1 A ector is a quantity that has both magnitude and direction. A ector is often represented by an arrow

More information

Chapter 3 Vectors in Physics

Chapter 3 Vectors in Physics Chapter 3 Vectors in Physics Is 1+1 always =2? Not true for vectors. Direction matters. Vectors in opposite directions can partially cancel. Position vectors, displacement, velocity, momentum, and forces

More information

Chapter 8: Polar Coordinates and Vectors

Chapter 8: Polar Coordinates and Vectors Chapter 8: Polar Coordinates and Vectors 8.1 Polar Coordinates This is another way (in addition to the x-y system) of specifying the position of a point in the plane. We give the distance r of the point

More information

Introduction to Mathematica and Graphing in 3-Space

Introduction to Mathematica and Graphing in 3-Space 1 Mathematica is a powerful tool that can be used to carry out computations and construct graphs and images to help deepen our understanding of mathematical concepts. This document will serve as a living

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

1.1 Bound and Free Vectors. 1.2 Vector Operations

1.1 Bound and Free Vectors. 1.2 Vector Operations 1 Vectors Vectors are used when both the magnitude and the direction of some physical quantity are required. Examples of such quantities are velocity, acceleration, force, electric and magnetic fields.

More information

VECTORS. Given two vectors! and! we can express the law of vector addition geometrically. + = Fig. 1 Geometrical definition of vector addition

VECTORS. Given two vectors! and! we can express the law of vector addition geometrically. + = Fig. 1 Geometrical definition of vector addition VECTORS Vectors in 2- D and 3- D in Euclidean space or flatland are easy compared to vectors in non- Euclidean space. In Cartesian coordinates we write a component of a vector as where the index i stands

More information

12.1. Cartesian Space

12.1. Cartesian Space 12.1. Cartesian Space In most of your previous math classes, we worked with functions on the xy-plane only meaning we were working only in 2D. Now we will be working in space, or rather 3D. Now we will

More information

Mechanics: Scalars and Vectors

Mechanics: Scalars and Vectors Mechanics: Scalars and Vectors Scalar Onl magnitude is associated with it Vector e.g., time, volume, densit, speed, energ, mass etc. Possess direction as well as magnitude Parallelogram law of addition

More information

GEOMETRY AND VECTORS

GEOMETRY AND VECTORS GEOMETRY AND VECTORS Distinguishing Between Points in Space One Approach Names: ( Fred, Steve, Alice...) Problem: distance & direction must be defined point-by-point More elegant take advantage of geometry

More information

Section 3.9. Matrix Norm

Section 3.9. Matrix Norm 3.9. Matrix Norm 1 Section 3.9. Matrix Norm Note. We define several matrix norms, some similar to vector norms and some reflecting how multiplication by a matrix affects the norm of a vector. We use matrix

More information

Linear Algebra. 1.1 Introduction to vectors 1.2 Lengths and dot products. January 28th, 2013 Math 301. Monday, January 28, 13

Linear Algebra. 1.1 Introduction to vectors 1.2 Lengths and dot products. January 28th, 2013 Math 301. Monday, January 28, 13 Linear Algebra 1.1 Introduction to vectors 1.2 Lengths and dot products January 28th, 2013 Math 301 Notation for linear systems 12w +4x + 23y +9z =0 2u + v +5w 2x +2y +8z =1 5u + v 6w +2x +4y z =6 8u 4v

More information

The American School of Marrakesh. Algebra 2 Algebra 2 Summer Preparation Packet

The American School of Marrakesh. Algebra 2 Algebra 2 Summer Preparation Packet The American School of Marrakesh Algebra Algebra Summer Preparation Packet Summer 016 Algebra Summer Preparation Packet This summer packet contains eciting math problems designed to ensure our readiness

More information

Vectors Part 1: Two Dimensions

Vectors Part 1: Two Dimensions Vectors Part 1: Two Dimensions Last modified: 20/02/2018 Links Scalars Vectors Definition Notation Polar Form Compass Directions Basic Vector Maths Multiply a Vector by a Scalar Unit Vectors Example Vectors

More information

Vectors a vector is a quantity that has both a magnitude (size) and a direction

Vectors a vector is a quantity that has both a magnitude (size) and a direction Vectors In physics, a vector is a quantity that has both a magnitude (size) and a direction. Familiar examples of vectors include velocity, force, and electric field. For any applications beyond one dimension,

More information

Section 8.1 Vector and Parametric Equations of a Line in

Section 8.1 Vector and Parametric Equations of a Line in Section 8.1 Vector and Parametric Equations of a Line in R 2 In this section, we begin with a discussion about how to find the vector and parametric equations of a line in R 2. To find the vector and parametric

More information

MTAEA Vectors in Euclidean Spaces

MTAEA Vectors in Euclidean Spaces School of Economics, Australian National University January 25, 2010 Vectors. Economists usually work in the vector space R n. A point in this space is called a vector, and is typically defined by its

More information

An Introduction to Systems of Equations

An Introduction to Systems of Equations LESSON 17 An Introduction to Sstems of Equations LEARNING OBJECTIVES Toda I am: completing the Desmos activit Sstems of Two Linear Equations. So that I can: write and solve a sstem of two linear equations

More information

MathQuest: Linear Algebra

MathQuest: Linear Algebra MathQuest: Linear Algebra Linear Independence. True or False The following vectors are linearly independent: (,0,0), (0,0,2), (3,0,) 2. Which set of vectors is linearly independent? (a) (2,3),(8,2) (b)

More information

Parametric Equations, Vectors, and Vector Valued Functions. Different parametric equations can yield the same curve:

Parametric Equations, Vectors, and Vector Valued Functions. Different parametric equations can yield the same curve: Parametric Equations, Vectors, and Vector Valued Functions Different parametric equations can yield the same curve: x=t, y=t 2 for t in [ 1,1] and x=t 3, y=t 6 for t in [ 1,1] give the same parabolic arc,

More information

Lesson 1: Inverses of Functions Lesson 2: Graphs of Polynomial Functions Lesson 3: 3-Dimensional Space

Lesson 1: Inverses of Functions Lesson 2: Graphs of Polynomial Functions Lesson 3: 3-Dimensional Space Table of Contents Introduction.............................................................. v Unit 1: Modeling with Matrices... 1 Lesson 2: Solving Problems Using Matrices.................................

More information

Detailed objectives are given in each of the sections listed below. 1. Cartesian Space Coordinates. 2. Displacements, Forces, Velocities and Vectors

Detailed objectives are given in each of the sections listed below. 1. Cartesian Space Coordinates. 2. Displacements, Forces, Velocities and Vectors Unit 1 Vectors In this unit, we introduce vectors, vector operations, and equations of lines and planes. Note: Unit 1 is based on Chapter 12 of the textbook, Salas and Hille s Calculus: Several Variables,

More information

Chapter 2. Linear Algebra. rather simple and learning them will eventually allow us to explain the strange results of

Chapter 2. Linear Algebra. rather simple and learning them will eventually allow us to explain the strange results of Chapter 2 Linear Algebra In this chapter, we study the formal structure that provides the background for quantum mechanics. The basic ideas of the mathematical machinery, linear algebra, are rather simple

More information

Chapter 11 Parametric Equations, Polar Curves, and Conic Sections

Chapter 11 Parametric Equations, Polar Curves, and Conic Sections Chapter 11 Parametric Equations, Polar Curves, and Conic Sections ü 11.1 Parametric Equations Students should read Sections 11.1-11. of Rogawski's Calculus [1] for a detailed discussion of the material

More information

Introduction to vectors

Introduction to vectors Lecture 4 Introduction to vectors Course website: http://facult.uml.edu/andri_danlov/teaching/phsicsi Lecture Capture: http://echo360.uml.edu/danlov2013/phsics1fall.html 95.141, Fall 2013, Lecture 3 Outline

More information

Definition: A vector is a directed line segment which represents a displacement from one point P to another point Q.

Definition: A vector is a directed line segment which represents a displacement from one point P to another point Q. THE UNIVERSITY OF NEW SOUTH WALES SCHOOL OF MATHEMATICS AND STATISTICS MATH Algebra Section : - Introduction to Vectors. You may have already met the notion of a vector in physics. There you will have

More information

Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems

Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems. Three-Dimensional Coordinate Systems To locate a point in a plane, two numbers are necessary. We know that any point in the plane can be represented as an ordered pair (a, b) of real numbers, where a is the x-coordinate and b is the y-coordinate.

More information

Vector Algebra August 2013

Vector Algebra August 2013 Vector Algebra 12.1 12.2 28 August 2013 What is a Vector? A vector (denoted or v) is a mathematical object possessing both: direction and magnitude also called length (denoted ). Vectors are often represented

More information

H.Algebra 2 Summer Review Packet

H.Algebra 2 Summer Review Packet H.Algebra Summer Review Packet 1 Correlation of Algebra Summer Packet with Algebra 1 Objectives A. Simplifing Polnomial Epressions Objectives: The student will be able to: Use the commutative, associative,

More information

14.1 Systems of Linear Equations in Two Variables

14.1 Systems of Linear Equations in Two Variables 86 Chapter 1 Sstems of Equations and Matrices 1.1 Sstems of Linear Equations in Two Variables Use the method of substitution to solve sstems of equations in two variables. Use the method of elimination

More information

Solution. The relationship between cartesian coordinates (x, y) and polar coordinates (r, θ) is given by. (x, y) = (r cos θ, r sin θ).

Solution. The relationship between cartesian coordinates (x, y) and polar coordinates (r, θ) is given by. (x, y) = (r cos θ, r sin θ). Problem 1. Let p 1 be the point having polar coordinates r = 1 and θ = π. Let p 2 be the point having polar coordinates r = 1 and θ = π/2. Find the Euclidean distance between p 1 and p 2. The relationship

More information

Linear Algebra Homework and Study Guide

Linear Algebra Homework and Study Guide Linear Algebra Homework and Study Guide Phil R. Smith, Ph.D. February 28, 20 Homework Problem Sets Organized by Learning Outcomes Test I: Systems of Linear Equations; Matrices Lesson. Give examples of

More information

Algebra II Notes Unit Five: Quadratic Functions. Syllabus Objectives: 5.1 The student will graph quadratic functions with and without technology.

Algebra II Notes Unit Five: Quadratic Functions. Syllabus Objectives: 5.1 The student will graph quadratic functions with and without technology. Sllabus Objectives:.1 The student will graph quadratic functions with and without technolog. Quadratic Function: a function that can be written in the form are real numbers Parabola: the U-shaped graph

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

Solutions of Linear system, vector and matrix equation

Solutions of Linear system, vector and matrix equation Goals: Solutions of Linear system, vector and matrix equation Solutions of linear system. Vectors, vector equation. Matrix equation. Math 112, Week 2 Suggested Textbook Readings: Sections 1.3, 1.4, 1.5

More information

Algebra II Notes Unit Four: Matrices and Determinants

Algebra II Notes Unit Four: Matrices and Determinants Syllabus Objectives: 4. The student will organize data using matrices. 4.2 The student will simplify matrix expressions using the properties of matrices. Matrix: a rectangular arrangement of numbers (called

More information

Outline. Linear Algebra for Computer Vision

Outline. Linear Algebra for Computer Vision Outline Linear Algebra for Computer Vision Introduction CMSC 88 D Notation and Basics Motivation Linear systems of equations Gauss Elimination, LU decomposition Linear Spaces and Operators Addition, scalar

More information

Vector Calculus Review

Vector Calculus Review Course Instructor Dr. Ramond C. Rumpf Office: A-337 Phone: (915) 747-6958 E-Mail: rcrumpf@utep.edu Vector Calculus Review EE3321 Electromagnetic Field Theor Outline Mathematical Preliminaries Phasors,

More information

Linear Programming. Maximize the function. P = Ax + By + C. subject to the constraints. a 1 x + b 1 y < c 1 a 2 x + b 2 y < c 2

Linear Programming. Maximize the function. P = Ax + By + C. subject to the constraints. a 1 x + b 1 y < c 1 a 2 x + b 2 y < c 2 Linear Programming Man real world problems require the optimization of some function subject to a collection of constraints. Note: Think of optimizing as maimizing or minimizing for MATH1010. For eample,

More information

Vectors. In kinematics, the simplest concept is position, so let s begin with a position vector shown below:

Vectors. In kinematics, the simplest concept is position, so let s begin with a position vector shown below: Vectors Extending the concepts of kinematics into two and three dimensions, the idea of a vector becomes very useful. By definition, a vector is a quantity with both a magnitude and a spatial direction.

More information

Physics 40 Chapter 3: Vectors

Physics 40 Chapter 3: Vectors Physics 40 Chapter 3: Vectors Cartesian Coordinate System Also called rectangular coordinate system x-and y- axes intersect at the origin Points are labeled (x,y) Polar Coordinate System Origin and reference

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

Lesson 7. Chapter 3: Two-Dimensional Kinematics COLLEGE PHYSICS VECTORS. Video Narrated by Jason Harlow, Physics Department, University of Toronto

Lesson 7. Chapter 3: Two-Dimensional Kinematics COLLEGE PHYSICS VECTORS. Video Narrated by Jason Harlow, Physics Department, University of Toronto COLLEGE PHYSICS Chapter 3: Two-Dimensional Kinematics Lesson 7 Video Narrated by Jason Harlow, Physics Department, University of Toronto VECTORS A quantity having both a magnitude and a direction is called

More information

Physics 170 Lecture 2. Phys 170 Lecture 2 1

Physics 170 Lecture 2. Phys 170 Lecture 2 1 Physics 170 Lecture 2 Phys 170 Lecture 2 1 Phys 170 Lecture 2 2 dministrivia Registration issues? Web page issues? On Connect? http://www.physics.ubc.ca/~mattison/courses/phys170 Mastering Engineering

More information

Scalar & Vector tutorial

Scalar & Vector tutorial Scalar & Vector tutorial scalar vector only magnitude, no direction both magnitude and direction 1-dimensional measurement of quantity not 1-dimensional time, mass, volume, speed temperature and so on

More information

Vector components and motion

Vector components and motion Vector components and motion Objectives Distinguish between vectors and scalars and give examples of each. Use vector diagrams to interpret the relationships among vector quantities such as force and acceleration.

More information

Math Week 1 notes

Math Week 1 notes Math 2270-004 Week notes We will not necessarily finish the material from a given day's notes on that day. Or on an amazing day we may get farther than I've predicted. We may also add or subtract some

More information

General Physics I, Spring Vectors

General Physics I, Spring Vectors General Physics I, Spring 2011 Vectors 1 Vectors: Introduction A vector quantity in physics is one that has a magnitude (absolute value) and a direction. We have seen three already: displacement, velocity,

More information

Graph the linear system and estimate the solution. Then check the solution algebraically.

Graph the linear system and estimate the solution. Then check the solution algebraically. (Chapters and ) A. Linear Sstems (pp. 6 0). Solve a Sstem b Graphing Vocabular Solution For a sstem of linear equations in two variables, an ordered pair (x, ) that satisfies each equation. Consistent

More information

Projectile Motion and 2-D Dynamics

Projectile Motion and 2-D Dynamics Projectile Motion and 2-D Dynamics Vector Notation Vectors vs. Scalars In Physics 11, you learned the difference between vectors and scalars. A vector is a quantity that includes both direction and magnitude

More information

VECTORS IN THREE DIMENSIONS

VECTORS IN THREE DIMENSIONS 1 CHAPTER 2. BASIC TRIGONOMETRY 1 INSTITIÚID TEICNEOLAÍOCHTA CHEATHARLACH INSTITUTE OF TECHNOLOGY CARLOW VECTORS IN THREE DIMENSIONS 1 Vectors in Two Dimensions A vector is an object which has magnitude

More information