An Elementary System of Axioms for Euclidean Geometry Based on Symmetry Principles
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The Parallelogram Law Objective: to Take Students Through the Process
The Parallelogram Law Objective: To take students through the process of discovery, making a conjecture, further exploration, and finally proof. I. Introduction: Use one of the following… • Geometer’s Sketchpad demonstration • Geogebra demonstration • The introductory handout from this lesson Using one of the introductory activities, allow students to explore and make a conjecture about the relationship between the sum of the squares of the sides of a parallelogram and the sum of the squares of the diagonals. Conjecture: The sum of the squares of the sides of a parallelogram equals the sum of the squares of the diagonals. Ask the question: Can we prove this is always true? II. Activity: Have students look at one more example. Follow the instructions on the exploration handouts, “Demonstrating the Parallelogram Law.” • Give each student a copy of the student handouts, scissors, a glue stick, and two different colored highlighters. Have students follow the instructions. When they get toward the end, they will need to cut very small pieces to fit in the uncovered space. Most likely there will be a very small amount of space left uncovered, or a small amount will extend outside the figure. • After the activity, discuss the results. Did the squares along the two diagonals fit into the squares along all four sides? Since it is unlikely that it will fit exactly, students might question if the relationship is always true. At this point, talk about how we will need to find a convincing proof. III. Go through one or more of the proofs below: Page 1 of 10 MCC@WCCUSD 02/26/13 A. -
CHAPTER 3. VECTOR ALGEBRA Part 1: Addition and Scalar
CHAPTER 3. VECTOR ALGEBRA Part 1: Addition and Scalar Multiplication for Vectors. §1. Basics. Geometric or physical quantities such as length, area, volume, tempera- ture, pressure, speed, energy, capacity etc. are given by specifying a single numbers. Such quantities are called scalars, because many of them can be measured by tools with scales. Simply put, a scalar is just a number. Quantities such as force, velocity, acceleration, momentum, angular velocity, electric or magnetic field at a point etc are vector quantities, which are represented by an arrow. If the ‘base’ and the ‘head’ of this arrow are B and H repectively, then we denote this vector by −−→BH: Figure 1. Often we use a single block letter in lower case, such as u, v, w, p, q, r etc. to denote a vector. Thus, if we also use v to denote the above vector −−→BH, then v = −−→BH.A vector v has two ingradients: magnitude and direction. The magnitude is the length of the arrow representing v, and is denoted by v . In case v = −−→BH, certainly we | | have v = −−→BH for the magnitude of v. The meaning of the direction of a vector is | | | | self–evident. Two vectors are considered to be equal if they have the same magnitude and direction. You recognize two equal vectors in drawing, if their representing arrows are parallel to each other, pointing in the same way, and have the same length 1 Figure 2. For example, if A, B, C, D are vertices of a parallelogram, followed in that order, then −→AB = −−→DC and −−→AD = −−→BC: Figure 3. -
Linear Algebra for Dummies
Linear Algebra for Dummies Jorge A. Menendez October 6, 2017 Contents 1 Matrices and Vectors1 2 Matrix Multiplication2 3 Matrix Inverse, Pseudo-inverse4 4 Outer products 5 5 Inner Products 5 6 Example: Linear Regression7 7 Eigenstuff 8 8 Example: Covariance Matrices 11 9 Example: PCA 12 10 Useful resources 12 1 Matrices and Vectors An m × n matrix is simply an array of numbers: 2 3 a11 a12 : : : a1n 6 a21 a22 : : : a2n 7 A = 6 7 6 . 7 4 . 5 am1 am2 : : : amn where we define the indexing Aij = aij to designate the component in the ith row and jth column of A. The transpose of a matrix is obtained by flipping the rows with the columns: 2 3 a11 a21 : : : an1 6 a12 a22 : : : an2 7 AT = 6 7 6 . 7 4 . 5 a1m a2m : : : anm T which evidently is now an n × m matrix, with components Aij = Aji = aji. In other words, the transpose is obtained by simply flipping the row and column indeces. One particularly important matrix is called the identity matrix, which is composed of 1’s on the diagonal and 0’s everywhere else: 21 0 ::: 03 60 1 ::: 07 6 7 6. .. .7 4. .5 0 0 ::: 1 1 It is called the identity matrix because the product of any matrix with the identity matrix is identical to itself: AI = A In other words, I is the equivalent of the number 1 for matrices. For our purposes, a vector can simply be thought of as a matrix with one column1: 2 3 a1 6a2 7 a = 6 7 6 . -
Equations of Lines and Planes
Equations of Lines and 12.5 Planes Copyright © Cengage Learning. All rights reserved. Lines A line in the xy-plane is determined when a point on the line and the direction of the line (its slope or angle of inclination) are given. The equation of the line can then be written using the point-slope form. Likewise, a line L in three-dimensional space is determined when we know a point P0(x0, y0, z0) on L and the direction of L. In three dimensions the direction of a line is conveniently described by a vector, so we let v be a vector parallel to L. 2 Lines Let P(x, y, z) be an arbitrary point on L and let r0 and r be the position vectors of P0 and P (that is, they have representations and ). If a is the vector with representation as in Figure 1, then the Triangle Law for vector addition gives r = r0 + a. Figure 1 3 Lines But, since a and v are parallel vectors, there is a scalar t such that a = t v. Thus which is a vector equation of L. Each value of the parameter t gives the position vector r of a point on L. In other words, as t varies, the line is traced out by the tip of the vector r. 4 Lines As Figure 2 indicates, positive values of t correspond to points on L that lie on one side of P0, whereas negative values of t correspond to points that lie on the other side of P0. -
Lecture 3.Pdf
ENGR-1100 Introduction to Engineering Analysis Lecture 3 POSITION VECTORS & FORCE VECTORS Today’s Objectives: Students will be able to : a) Represent a position vector in Cartesian coordinate form, from given geometry. In-Class Activities: • Applications / b) Represent a force vector directed along Relevance a line. • Write Position Vectors • Write a Force Vector along a line 1 DOT PRODUCT Today’s Objective: Students will be able to use the vector dot product to: a) determine an angle between In-Class Activities: two vectors, and, •Applications / Relevance b) determine the projection of a vector • Dot product - Definition along a specified line. • Angle Determination • Determining the Projection APPLICATIONS This ship’s mooring line, connected to the bow, can be represented as a Cartesian vector. What are the forces in the mooring line and how do we find their directions? Why would we want to know these things? 2 APPLICATIONS (continued) This awning is held up by three chains. What are the forces in the chains and how do we find their directions? Why would we want to know these things? POSITION VECTOR A position vector is defined as a fixed vector that locates a point in space relative to another point. Consider two points, A and B, in 3-D space. Let their coordinates be (XA, YA, ZA) and (XB, YB, ZB), respectively. 3 POSITION VECTOR The position vector directed from A to B, rAB , is defined as rAB = {( XB –XA ) i + ( YB –YA ) j + ( ZB –ZA ) k }m Please note that B is the ending point and A is the starting point. -
Exercise 7.5
IN SUMMARY Key Idea • A projection of one vector onto another can be either a scalar or a vector. The difference is the vector projection has a direction. A A a a u u O O b NB b N B Scalar projection of a on b Vector projection of a on b Need to Know ! ! ! ! a # b ! • The scalar projection of a on b ϭϭ! 0 a 0 cos u, where u is the angle @ b @ ! ! between a and b. ! ! ! ! ! ! a # b ! a # b ! • The vector projection of a on b ϭ ! b ϭ a ! ! b b @ b @ 2 b # b ! • The direction cosines for OP ϭ 1a, b, c2 are a b cos a ϭ , cos b ϭ , 2 2 2 2 2 2 Va ϩ b ϩ c Va ϩ b ϩ c c cos g ϭ , where a, b, and g are the direction angles 2 2 2 Va ϩ b ϩ c ! between the position vector OP and the positive x-axis, y-axis and z-axis, respectively. Exercise 7.5 PART A ! 1. a. The vector a ϭ 12, 32 is projected onto the x-axis. What is the scalar projection? What is the vector projection? ! b. What are the scalar and vector projections when a is projected onto the y-axis? 2. Explain why it is not possible to obtain! either a scalar! projection or a vector projection when a nonzero vector x is projected on 0. 398 7.5 SCALAR AND VECTOR PROJECTIONS NEL ! ! 3. Consider two nonzero vectors,a and b, that are perpendicular! ! to each other.! Explain why the scalar and vector projections of a on b must! be !0 and 0, respectively. -
MATH 304 Linear Algebra Lecture 24: Scalar Product. Vectors: Geometric Approach
MATH 304 Linear Algebra Lecture 24: Scalar product. Vectors: geometric approach B A B′ A′ A vector is represented by a directed segment. • Directed segment is drawn as an arrow. • Different arrows represent the same vector if • they are of the same length and direction. Vectors: geometric approach v B A v B′ A′ −→AB denotes the vector represented by the arrow with tip at B and tail at A. −→AA is called the zero vector and denoted 0. Vectors: geometric approach v B − A v B′ A′ If v = −→AB then −→BA is called the negative vector of v and denoted v. − Vector addition Given vectors a and b, their sum a + b is defined by the rule −→AB + −→BC = −→AC. That is, choose points A, B, C so that −→AB = a and −→BC = b. Then a + b = −→AC. B b a C a b + B′ b A a C ′ a + b A′ The difference of the two vectors is defined as a b = a + ( b). − − b a b − a Properties of vector addition: a + b = b + a (commutative law) (a + b) + c = a + (b + c) (associative law) a + 0 = 0 + a = a a + ( a) = ( a) + a = 0 − − Let −→AB = a. Then a + 0 = −→AB + −→BB = −→AB = a, a + ( a) = −→AB + −→BA = −→AA = 0. − Let −→AB = a, −→BC = b, and −→CD = c. Then (a + b) + c = (−→AB + −→BC) + −→CD = −→AC + −→CD = −→AD, a + (b + c) = −→AB + (−→BC + −→CD) = −→AB + −→BD = −→AD. Parallelogram rule Let −→AB = a, −→BC = b, −−→AB′ = b, and −−→B′C ′ = a. Then a + b = −→AC, b + a = −−→AC ′. -
Ill.'Dept. of Mathemat Available in Hard Copy Due To:Copyright,Restrictions
Docusty4 REWIRE . ED184843 E 030 460 AUTHOR Kogan, B. Yu TITLE The Application àf Me anics to Ge setry. Popullr Lectures in Mathematice. 'INSTITUTION Cbicag Univ. Ill.'Dept. of Mathemat s. SPONS AGENCY National Science Foundation, Nashington;.D.C. PUB DATE 74 GRANT NSLY-3-13847(MA) NOTE 65p.; ?or related documents, see SE 030 4-61-465. Not available in hard copy due to:copyright,restrictions. Translated and adapted from the Russian edition. 'AVAILABLE FROM The University of Chicago Press, Chicaip, IL 60637. (Order No. 450163; $4.50). EDRS PRICE MP01 Plus Postage.. PC Not Available from ED4S. DESZRIPTORS *College Mathematics; Force; Geometric Concepti; *Geometry; Higher Education; Lecture Method; *Mathematical Applications; *Mathemaiics; *Mechanics (Physics) ABBTRAiT Presented in thir traInslktion are three chapters. Chapter I discusses the compbsitivn of forces and several theoreas of geometry are proved using the'fundamental conceptsand certain laws of statics. Chapter II discusses the perpetual motion postRlate; several geometri:l.theorems are proved, uting the postulate t4t p9rp ual motion is iipossib?e. In Chapter ILI,' the Center of Gray Potential Energy, and Vork are discussed. (MK) a N'4 , * Reproductions supplied by EDRS are the best that can be madel * * from the original document. * U.S. DIEPARTMINT OP WEALTH. g.tpUCATION WILPARI - aATIONAL INSTITTLISM Oa IDUCATION THIS DOCUMENT HAS BEEN REPRO. atiCED EXACTLMAIS RECEIVED Flicw THE PERSON OR ORGANIZATION DRPOIN- ATINO IT POINTS'OF VIEW OR OPINIONS STATED DO NOT NECESSARILY WEPRE.' se NT OFFICIAL NATIONAL INSTITUTE OF EDUCATION POSITION OR POLICY 0 * "PERMISSION TO REPRODUC THIS MATERIAL IN MICROFICHE dIlLY HAS SEEN GRANTED BY TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC)." -Mlk -1 Popular Lectures In nithematics. -
Basics of Linear Algebra
Basics of Linear Algebra Jos and Sophia Vectors ● Linear Algebra Definition: A list of numbers with a magnitude and a direction. ○ Magnitude: a = [4,3] |a| =sqrt(4^2+3^2)= 5 ○ Direction: angle vector points ● Computer Science Definition: A list of numbers. ○ Example: Heights = [60, 68, 72, 67] Dot Product of Vectors Formula: a · b = |a| × |b| × cos(θ) ● Definition: Multiplication of two vectors which results in a scalar value ● In the diagram: ○ |a| is the magnitude (length) of vector a ○ |b| is the magnitude of vector b ○ Θ is the angle between a and b Matrix ● Definition: ● Matrix elements: ● a)Matrix is an arrangement of numbers into rows and columns. ● b) A matrix is an m × n array of scalars from a given field F. The individual values in the matrix are called entries. ● Matrix dimensions: the number of rows and columns of the matrix, in that order. Multiplication of Matrices ● The multiplication of two matrices ● Result matrix dimensions ○ Notation: (Row, Column) ○ Columns of the 1st matrix must equal the rows of the 2nd matrix ○ Result matrix is equal to the number of (1, 2, 3) • (7, 9, 11) = 1×7 +2×9 + 3×11 rows in 1st matrix and the number of = 58 columns in the 2nd matrix ○ Ex. 3 x 4 ॱ 5 x 3 ■ Dot product does not work ○ Ex. 5 x 3 ॱ 3 x 4 ■ Dot product does work ■ Result: 5 x 4 Dot Product Application ● Application: Ray tracing program ○ Quickly create an image with lower quality ○ “Refinement rendering pass” occurs ■ Removes the jagged edges ○ Dot product used to calculate ■ Intersection between a ray and a sphere ■ Measure the length to the intersection points ● Application: Forward Propagation ○ Input matrix * weighted matrix = prediction matrix http://immersivemath.com/ila/ch03_dotprodu ct/ch03.html#fig_dp_ray_tracer Projections One important use of dot products is in projections. -
Fundamental Theorems in Mathematics
SOME FUNDAMENTAL THEOREMS IN MATHEMATICS OLIVER KNILL Abstract. An expository hitchhikers guide to some theorems in mathematics. Criteria for the current list of 243 theorems are whether the result can be formulated elegantly, whether it is beautiful or useful and whether it could serve as a guide [6] without leading to panic. The order is not a ranking but ordered along a time-line when things were writ- ten down. Since [556] stated “a mathematical theorem only becomes beautiful if presented as a crown jewel within a context" we try sometimes to give some context. Of course, any such list of theorems is a matter of personal preferences, taste and limitations. The num- ber of theorems is arbitrary, the initial obvious goal was 42 but that number got eventually surpassed as it is hard to stop, once started. As a compensation, there are 42 “tweetable" theorems with included proofs. More comments on the choice of the theorems is included in an epilogue. For literature on general mathematics, see [193, 189, 29, 235, 254, 619, 412, 138], for history [217, 625, 376, 73, 46, 208, 379, 365, 690, 113, 618, 79, 259, 341], for popular, beautiful or elegant things [12, 529, 201, 182, 17, 672, 673, 44, 204, 190, 245, 446, 616, 303, 201, 2, 127, 146, 128, 502, 261, 172]. For comprehensive overviews in large parts of math- ematics, [74, 165, 166, 51, 593] or predictions on developments [47]. For reflections about mathematics in general [145, 455, 45, 306, 439, 99, 561]. Encyclopedic source examples are [188, 705, 670, 102, 192, 152, 221, 191, 111, 635]. -
The Dot Product
Lecture 3: The Dot Product 3.1 The angle between vectors 2 Suppose x = (x1; x2) and y = (y1; y2) are two vectors in R , neither of which is the zero vector 0. Let α and β be the angles between x and y and the positive horizontal axis, respectively, measured in the counterclockwise direction. Supposing α β, let θ = α β. Then θ is the angle between x and y measured in the counterclockwise≥ direction. From− the subtraction formula for cosine we have cos(θ) = cos(α β) = cos(α) cos(β) + sin(α) sin(β): − Now x cos(α) = 1 ; x j j y cos(β) = 1 ; y j j x sin(α) = 2 ; x j j and y sin(β) = 2 : y j j Thus, we have x y x y x y + x y cos(θ) = 1 1 + 2 2 = 1 1 2 2 : x y x y x y j jj j j jj j j jj j θ α β The angle between two vectors in R2 Example Let θ be the smallest angle between x = (2; 1) and y = (1; 3), measured in the counterclockwise direction. Then (2)(1) + (1)(3) 5 1 cos(θ) = = = : x y p5p10 p2 j jj j 3-1 Lecture 3: The Dot Product 3-2 Hence 1 1 π θ = cos− = : p2 4 With more work it is possible to show that if x = (x1; x2; x3) and y = (y1; y2; y3) are two vectors in R3, neither of which is the zero vector 0, and θ is the smallest positive angle between x and y, then x y + x y + x y cos(θ) = 1 1 2 2 3 3 x y j jj j 3.2 The dot product n Definition If x = (x1; x2; : : : ; xn) and y = (y1; y2; : : : ; yn) are vectors in R , then the dot product of x and y, denoted x y, is given by · x y = x1y1 + x2y2 + + xnyn: · ··· Note that the dot product of two vectors is a scalar, not another vector. -
Ruler and Compass Constructions and Abstract Algebra
Ruler and Compass Constructions and Abstract Algebra Introduction Around 300 BC, Euclid wrote a series of 13 books on geometry and number theory. These books are collectively called the Elements and are some of the most famous books ever written about any subject. In the Elements, Euclid described several “ruler and compass” constructions. By ruler, we mean a straightedge with no marks at all (so it does not look like the rulers with centimeters or inches that you get at the store). The ruler allows you to draw the (unique) line between two (distinct) given points. The compass allows you to draw a circle with a given point as its center and with radius equal to the distance between two given points. But there are three famous constructions that the Greeks could not perform using ruler and compass: • Doubling the cube: constructing a cube having twice the volume of a given cube. • Trisecting the angle: constructing an angle 1/3 the measure of a given angle. • Squaring the circle: constructing a square with area equal to that of a given circle. The Greeks were able to construct several regular polygons, but another famous problem was also beyond their reach: • Determine which regular polygons are constructible with ruler and compass. These famous problems were open (unsolved) for 2000 years! Thanks to the modern tools of abstract algebra, we now know the solutions: • It is impossible to double the cube, trisect the angle, or square the circle using only ruler (straightedge) and compass. • We also know precisely which regular polygons can be constructed and which ones cannot.