SlideShare uma empresa Scribd logo
1 de 30
Using Matrices to Transform
Geometric Figures
                   Warm Up
                   Lesson Presentation
                   Lesson Quiz
Warm Up
Perform the indicated operation.

1.


2.


3.
Objective
Use matrices to transform a plane
figure.
Vocabulary
translation matrix
reflection matrix
rotation matrix
You can describe the position, shape, and size of a
polygon on a coordinate plane by naming the
ordered pairs that define its vertices.

The coordinates of ΔABC below are A (–2, –1),
B (0, 3), and C (1, –2) .

You can also define ΔABC by a matrix:

                  x-coordinates
                  y-coordinates
A translation matrix is a matrix used to
translate coordinates on the coordinate plane.
The matrix sum of a preimage and a translation
matrix gives the coordinates of the translated
image.
Reading Math
The prefix pre- means ―before,‖ so the preimage
is the original figure before any transformations
are applied. The image is the resulting figure
after a transformation.
Example 1: Using Matrices to Translate a Figure

 Translate ΔABC with coordinates A(–2, 1),
 B(3, 2), and C(0, –3), 3 units left and 4 units
 up. Find the coordinates of the vertices of
 the image, and graph.

The translation
matrix will have –3               x-coordinates
in all entries in row             y-coordinates
1 and 4 in all entries
in row 2.
Example 1 Continued




A'B'C', the image of
ABC, has coordinates
A'(–5, 5), B'(0, 6), and
C'(–3, 1).
Check It Out! Example 1

Translate ΔGHJ with coordinates G(2, 4), H(3,
1), and J(1, –1) 3 units right and 1 unit down.
Find the coordinates of the vertices of the image
and graph.

The translation
matrix will have 3 in            x-coordinates
all entries in row 1             y-coordinates
and –1 in all entries
in row 2.
Check It Out! Example 1 Continued




G'H'J', the image of
GHJ, has coordinates
G'(5, 3), H'(6, 0), and
J'(4, –2).
A dilation is a transformation that scales—enlarges
or reduces—the preimage, resulting in similar
figures. Remember that for similar figures, the
shape is the same but the size may be different.
Angles are congruent, and side lengths are
proportional.

When the center of dilation is the origin,
multiplying the coordinate matrix by a scalar gives
the coordinates of the dilated image. In this
lesson, all dilations assume that the origin is the
center of dilation.
Example 2: Using Matrices to Enlarge a Figure
Enlarge ΔABC with coordinates
A(2, 3), B(1, –2), and C(–3, 1), by a factor
of 2. Find the coordinates of the vertices of
the image, and graph.
Multiply each coordinate by 2 by multiplying each
entry by 2.




                           x-coordinates
                           y-coordinates
Example 2 Continued



A'B'C', the image of
ABC, has coordinates
A'(4, 6), B'(2, –4),
and C'(–6, 2).
Check It Out! Example 2
Enlarge ΔDEF with coordinates D(2, 3), E(5,
1), and F(–2, –7) a factor of . Find the
coordinates of the vertices of the image, and
graph.
Multiply each coordinate by   by multiplying each
entry by   .
Check It Out! Example 2 Continued




D'E'F', the image of
DEF, has coordinates
A reflection matrix is a matrix that creates a
mirror image by reflecting each vertex over a
specified line of symmetry. To reflect a figure
across the y-axis, multiply




by the coordinate matrix. This reverses the x-
coordinates and keeps the y-coordinates
unchanged.
Caution
Matrix multiplication is not commutative. So be
sure to keep the transformation matrix on the
left!
Example 3: Using Matrices to Reflect a Figure

Reflect ΔPQR with coordinates
P(2, 2), Q(2, –1), and R(4, 3) across the
y-axis. Find the coordinates of the
vertices of the image, and graph.




    Each x-coordinate is multiplied by –1.

    Each y-coordinate is multiplied by 1.
Example 3 Continued




The coordinates of the vertices of the image are
P'(–2, 2), Q'(–2, –1), and R'(–4, 3).
Check It Out! Example 3

To reflect a figure across the x-axis, multiply by

      .

Reflect ΔJKL with coordinates J(3, 4), K(4, 2),
and L(1, –2) across the x-axis. Find the
coordinates of the vertices of the image and
graph.
Check It Out! Example 3




The coordinates of the vertices of the image
are J'(3, –4), K'(4, –2), L'(1, 2).
A rotation matrix is a matrix used to rotate a
figure. Example 4 gives several types of rotation
matrices.
Example 4: Using Matrices to Rotate a Figure

Use each matrix to rotate polygon ABCD
with coordinates A(0, 1), B(2, –
4), C(5, 1), and D(2, 3) about the origin.
Graph and describe the image.
A.


The image A'B'C'D' is rotated 90° counterclockwise.

B.


The image A''B''C''D'' is rotated 90° clockwise.
Example 4 Continued
Check It Out! Example 4


Use

Rotate ΔABC with coordinates A(0, 0),
B(4, 0), and C(0, –3) about the origin.
Graph and describe the image.




A'(0, 0), B'(-4, 0), C'(0, 3); the image is rotated
180°.
Check It Out! Example 4 Continued
Lesson Quiz

Transform triangle PQR with vertices
P(–1, –1), Q(3, 1), R(0, 3). For each, show
the matrix transformation and state the
vertices of the image.
1. Translation 3 units to the left and 2 units up.

2. Dilation by a factor of 1.5.

3. Reflection across the x-axis.

4. 90° rotation, clockwise.
Lesson Quiz

1.



2.




3.        4.

Mais conteúdo relacionado

Mais procurados

Linear Algebra and Matrix
Linear Algebra and MatrixLinear Algebra and Matrix
Linear Algebra and Matrix
itutor
 
Function transformations
Function transformationsFunction transformations
Function transformations
Terry Gastauer
 
Matrix basic operations
Matrix basic operationsMatrix basic operations
Matrix basic operations
Jessica Garcia
 
Parabola
ParabolaParabola
Parabola
itutor
 
Solving systems of Linear Equations
Solving systems of Linear EquationsSolving systems of Linear Equations
Solving systems of Linear Equations
swartzje
 

Mais procurados (20)

Linear Algebra and Matrix
Linear Algebra and MatrixLinear Algebra and Matrix
Linear Algebra and Matrix
 
Function transformations
Function transformationsFunction transformations
Function transformations
 
Matrix basic operations
Matrix basic operationsMatrix basic operations
Matrix basic operations
 
Parabola
ParabolaParabola
Parabola
 
Differential geometry three dimensional space
Differential geometry   three dimensional spaceDifferential geometry   three dimensional space
Differential geometry three dimensional space
 
PRESENTATION ON INTRODUCTION TO SEVERAL VARIABLES AND PARTIAL DERIVATIVES
PRESENTATION ON INTRODUCTION TO SEVERAL VARIABLES AND PARTIAL DERIVATIVES   PRESENTATION ON INTRODUCTION TO SEVERAL VARIABLES AND PARTIAL DERIVATIVES
PRESENTATION ON INTRODUCTION TO SEVERAL VARIABLES AND PARTIAL DERIVATIVES
 
Determinants. Cramer’s Rule
Determinants. Cramer’s RuleDeterminants. Cramer’s Rule
Determinants. Cramer’s Rule
 
Graphs of linear equation
Graphs of linear equationGraphs of linear equation
Graphs of linear equation
 
Curve tracing
Curve tracingCurve tracing
Curve tracing
 
Presentation on matrix
Presentation on matrixPresentation on matrix
Presentation on matrix
 
Determinants
DeterminantsDeterminants
Determinants
 
Solving systems of Linear Equations
Solving systems of Linear EquationsSolving systems of Linear Equations
Solving systems of Linear Equations
 
Matrices and determinants-1
Matrices and determinants-1Matrices and determinants-1
Matrices and determinants-1
 
Integral calculus
Integral calculusIntegral calculus
Integral calculus
 
Two point form Equation of a line
Two point form Equation of a lineTwo point form Equation of a line
Two point form Equation of a line
 
Ppt on matrices and Determinants
Ppt on matrices and DeterminantsPpt on matrices and Determinants
Ppt on matrices and Determinants
 
Vector space
Vector spaceVector space
Vector space
 
Slope of a Line
Slope of a LineSlope of a Line
Slope of a Line
 
Matrix algebra
Matrix algebraMatrix algebra
Matrix algebra
 
3.8.1 Dilations and Scale Factor
3.8.1 Dilations and Scale Factor3.8.1 Dilations and Scale Factor
3.8.1 Dilations and Scale Factor
 

Destaque

Partial fractions
Partial fractionsPartial fractions
Partial fractions
Thivagar
 
The Google Pagerank algorithm - How does it work?
The Google Pagerank algorithm - How does it work?The Google Pagerank algorithm - How does it work?
The Google Pagerank algorithm - How does it work?
Kundan Bhaduri
 
Revision Partial Fractions
Revision   Partial FractionsRevision   Partial Fractions
Revision Partial Fractions
shmaths
 
QUADRATIC EQUATIONS
QUADRATIC EQUATIONSQUADRATIC EQUATIONS
QUADRATIC EQUATIONS
hiratufail
 
5 3 Partial Fractions
5 3 Partial Fractions5 3 Partial Fractions
5 3 Partial Fractions
silvia
 
Lesson 5: Matrix Algebra (slides)
Lesson 5: Matrix Algebra (slides)Lesson 5: Matrix Algebra (slides)
Lesson 5: Matrix Algebra (slides)
Matthew Leingang
 

Destaque (20)

Matrix TranceFormation
Matrix TranceFormationMatrix TranceFormation
Matrix TranceFormation
 
Page Rank
Page RankPage Rank
Page Rank
 
Phase and phase difference LO3
Phase and phase difference LO3Phase and phase difference LO3
Phase and phase difference LO3
 
Unit 7.4
Unit 7.4Unit 7.4
Unit 7.4
 
Partial fractions
Partial fractionsPartial fractions
Partial fractions
 
Partial Fractions Quadratic Term
Partial Fractions Quadratic TermPartial Fractions Quadratic Term
Partial Fractions Quadratic Term
 
The Google Pagerank algorithm - How does it work?
The Google Pagerank algorithm - How does it work?The Google Pagerank algorithm - How does it work?
The Google Pagerank algorithm - How does it work?
 
Partial Fraction
Partial FractionPartial Fraction
Partial Fraction
 
Google PageRank
Google PageRankGoogle PageRank
Google PageRank
 
Revision Partial Fractions
Revision   Partial FractionsRevision   Partial Fractions
Revision Partial Fractions
 
Matrices 1
Matrices 1Matrices 1
Matrices 1
 
QUADRATIC EQUATIONS
QUADRATIC EQUATIONSQUADRATIC EQUATIONS
QUADRATIC EQUATIONS
 
5 3 Partial Fractions
5 3 Partial Fractions5 3 Partial Fractions
5 3 Partial Fractions
 
Business maths
Business mathsBusiness maths
Business maths
 
direct and inverse variations
direct and inverse variationsdirect and inverse variations
direct and inverse variations
 
Manage Emosi Anda
Manage Emosi AndaManage Emosi Anda
Manage Emosi Anda
 
Google Page Rank Algorithm
Google Page Rank AlgorithmGoogle Page Rank Algorithm
Google Page Rank Algorithm
 
Scoring matrices
Scoring matricesScoring matrices
Scoring matrices
 
Lesson 5: Matrix Algebra (slides)
Lesson 5: Matrix Algebra (slides)Lesson 5: Matrix Algebra (slides)
Lesson 5: Matrix Algebra (slides)
 
Matrices
MatricesMatrices
Matrices
 

Semelhante a Matrix transformation

2001 transformations reflections etc
2001 transformations reflections etc2001 transformations reflections etc
2001 transformations reflections etc
jbianco9910
 
2001 transformations reflections etc
2001 transformations reflections etc2001 transformations reflections etc
2001 transformations reflections etc
jbianco9910
 
Transformations edmodo 2013
Transformations edmodo 2013Transformations edmodo 2013
Transformations edmodo 2013
shumwayc
 
8.6 reflections and symmetry 1
8.6 reflections and symmetry 18.6 reflections and symmetry 1
8.6 reflections and symmetry 1
bweldon
 
2002 more with transformations
2002 more with transformations2002 more with transformations
2002 more with transformations
jbianco9910
 

Semelhante a Matrix transformation (20)

Chapter 6
Chapter 6Chapter 6
Chapter 6
 
2001 transformations reflections etc
2001 transformations reflections etc2001 transformations reflections etc
2001 transformations reflections etc
 
2001 transformations reflections etc
2001 transformations reflections etc2001 transformations reflections etc
2001 transformations reflections etc
 
Geometry unit 9.5
Geometry unit 9.5Geometry unit 9.5
Geometry unit 9.5
 
Obj. 30 Reflections and Translations
Obj. 30 Reflections and TranslationsObj. 30 Reflections and Translations
Obj. 30 Reflections and Translations
 
Geometry unit 9.1
Geometry unit 9.1Geometry unit 9.1
Geometry unit 9.1
 
Transformations zambia
Transformations zambiaTransformations zambia
Transformations zambia
 
Transformations edmodo 2013
Transformations edmodo 2013Transformations edmodo 2013
Transformations edmodo 2013
 
8.6 reflections and symmetry 1
8.6 reflections and symmetry 18.6 reflections and symmetry 1
8.6 reflections and symmetry 1
 
2.6.1 Translations and Reflections
2.6.1 Translations and Reflections2.6.1 Translations and Reflections
2.6.1 Translations and Reflections
 
Transf handout
Transf handoutTransf handout
Transf handout
 
Geometry unit 9.6 9.7
Geometry unit 9.6 9.7Geometry unit 9.6 9.7
Geometry unit 9.6 9.7
 
(8) Lesson 6.1 - Translations
(8) Lesson 6.1 - Translations(8) Lesson 6.1 - Translations
(8) Lesson 6.1 - Translations
 
Translations (day 2)
Translations (day 2)Translations (day 2)
Translations (day 2)
 
(8) Lesson 6.2 - Reflections
(8) Lesson 6.2 - Reflections(8) Lesson 6.2 - Reflections
(8) Lesson 6.2 - Reflections
 
Transformations SLIDES and Notes ppt.ppt
Transformations  SLIDES and Notes ppt.pptTransformations  SLIDES and Notes ppt.ppt
Transformations SLIDES and Notes ppt.ppt
 
Transformations lower secondary fil..ppt
Transformations lower secondary fil..pptTransformations lower secondary fil..ppt
Transformations lower secondary fil..ppt
 
Translations11.6.12
Translations11.6.12Translations11.6.12
Translations11.6.12
 
Module 3 plane coordinate geometry
Module 3 plane coordinate geometryModule 3 plane coordinate geometry
Module 3 plane coordinate geometry
 
2002 more with transformations
2002 more with transformations2002 more with transformations
2002 more with transformations
 

Mais de mstf mstf (20)

Trigonometry by mstfdemirdag
Trigonometry by mstfdemirdagTrigonometry by mstfdemirdag
Trigonometry by mstfdemirdag
 
Functions by mstfdemirdag
Functions by mstfdemirdagFunctions by mstfdemirdag
Functions by mstfdemirdag
 
Trigonometric functions
Trigonometric functionsTrigonometric functions
Trigonometric functions
 
Quadratic functions
Quadratic functionsQuadratic functions
Quadratic functions
 
Sequences and series
Sequences and seriesSequences and series
Sequences and series
 
Functions
FunctionsFunctions
Functions
 
Pre geometry
Pre geometryPre geometry
Pre geometry
 
Solving linear equations in two
Solving linear equations in twoSolving linear equations in two
Solving linear equations in two
 
Natural numbers
Natural numbersNatural numbers
Natural numbers
 
Logic
LogicLogic
Logic
 
Density
DensityDensity
Density
 
Mechanics
MechanicsMechanics
Mechanics
 
Divisibility
DivisibilityDivisibility
Divisibility
 
Free fall
Free fallFree fall
Free fall
 
Prime numbers and factorization
Prime numbers and factorizationPrime numbers and factorization
Prime numbers and factorization
 
Exponents
ExponentsExponents
Exponents
 
Motion in two dimensions
Motion in two dimensionsMotion in two dimensions
Motion in two dimensions
 
Force
ForceForce
Force
 
Radicals
RadicalsRadicals
Radicals
 
Fractions
FractionsFractions
Fractions
 

Último

Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 

Último (20)

[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital Adaptability
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 

Matrix transformation

  • 1.
  • 2. Using Matrices to Transform Geometric Figures Warm Up Lesson Presentation Lesson Quiz
  • 3. Warm Up Perform the indicated operation. 1. 2. 3.
  • 4. Objective Use matrices to transform a plane figure.
  • 6. You can describe the position, shape, and size of a polygon on a coordinate plane by naming the ordered pairs that define its vertices. The coordinates of ΔABC below are A (–2, –1), B (0, 3), and C (1, –2) . You can also define ΔABC by a matrix:  x-coordinates  y-coordinates
  • 7. A translation matrix is a matrix used to translate coordinates on the coordinate plane. The matrix sum of a preimage and a translation matrix gives the coordinates of the translated image.
  • 8. Reading Math The prefix pre- means ―before,‖ so the preimage is the original figure before any transformations are applied. The image is the resulting figure after a transformation.
  • 9. Example 1: Using Matrices to Translate a Figure Translate ΔABC with coordinates A(–2, 1), B(3, 2), and C(0, –3), 3 units left and 4 units up. Find the coordinates of the vertices of the image, and graph. The translation matrix will have –3  x-coordinates in all entries in row  y-coordinates 1 and 4 in all entries in row 2.
  • 10. Example 1 Continued A'B'C', the image of ABC, has coordinates A'(–5, 5), B'(0, 6), and C'(–3, 1).
  • 11. Check It Out! Example 1 Translate ΔGHJ with coordinates G(2, 4), H(3, 1), and J(1, –1) 3 units right and 1 unit down. Find the coordinates of the vertices of the image and graph. The translation matrix will have 3 in  x-coordinates all entries in row 1  y-coordinates and –1 in all entries in row 2.
  • 12. Check It Out! Example 1 Continued G'H'J', the image of GHJ, has coordinates G'(5, 3), H'(6, 0), and J'(4, –2).
  • 13. A dilation is a transformation that scales—enlarges or reduces—the preimage, resulting in similar figures. Remember that for similar figures, the shape is the same but the size may be different. Angles are congruent, and side lengths are proportional. When the center of dilation is the origin, multiplying the coordinate matrix by a scalar gives the coordinates of the dilated image. In this lesson, all dilations assume that the origin is the center of dilation.
  • 14. Example 2: Using Matrices to Enlarge a Figure Enlarge ΔABC with coordinates A(2, 3), B(1, –2), and C(–3, 1), by a factor of 2. Find the coordinates of the vertices of the image, and graph. Multiply each coordinate by 2 by multiplying each entry by 2.  x-coordinates  y-coordinates
  • 15. Example 2 Continued A'B'C', the image of ABC, has coordinates A'(4, 6), B'(2, –4), and C'(–6, 2).
  • 16. Check It Out! Example 2 Enlarge ΔDEF with coordinates D(2, 3), E(5, 1), and F(–2, –7) a factor of . Find the coordinates of the vertices of the image, and graph. Multiply each coordinate by by multiplying each entry by .
  • 17. Check It Out! Example 2 Continued D'E'F', the image of DEF, has coordinates
  • 18. A reflection matrix is a matrix that creates a mirror image by reflecting each vertex over a specified line of symmetry. To reflect a figure across the y-axis, multiply by the coordinate matrix. This reverses the x- coordinates and keeps the y-coordinates unchanged.
  • 19. Caution Matrix multiplication is not commutative. So be sure to keep the transformation matrix on the left!
  • 20. Example 3: Using Matrices to Reflect a Figure Reflect ΔPQR with coordinates P(2, 2), Q(2, –1), and R(4, 3) across the y-axis. Find the coordinates of the vertices of the image, and graph. Each x-coordinate is multiplied by –1. Each y-coordinate is multiplied by 1.
  • 21. Example 3 Continued The coordinates of the vertices of the image are P'(–2, 2), Q'(–2, –1), and R'(–4, 3).
  • 22. Check It Out! Example 3 To reflect a figure across the x-axis, multiply by . Reflect ΔJKL with coordinates J(3, 4), K(4, 2), and L(1, –2) across the x-axis. Find the coordinates of the vertices of the image and graph.
  • 23. Check It Out! Example 3 The coordinates of the vertices of the image are J'(3, –4), K'(4, –2), L'(1, 2).
  • 24. A rotation matrix is a matrix used to rotate a figure. Example 4 gives several types of rotation matrices.
  • 25. Example 4: Using Matrices to Rotate a Figure Use each matrix to rotate polygon ABCD with coordinates A(0, 1), B(2, – 4), C(5, 1), and D(2, 3) about the origin. Graph and describe the image. A. The image A'B'C'D' is rotated 90° counterclockwise. B. The image A''B''C''D'' is rotated 90° clockwise.
  • 27. Check It Out! Example 4 Use Rotate ΔABC with coordinates A(0, 0), B(4, 0), and C(0, –3) about the origin. Graph and describe the image. A'(0, 0), B'(-4, 0), C'(0, 3); the image is rotated 180°.
  • 28. Check It Out! Example 4 Continued
  • 29. Lesson Quiz Transform triangle PQR with vertices P(–1, –1), Q(3, 1), R(0, 3). For each, show the matrix transformation and state the vertices of the image. 1. Translation 3 units to the left and 2 units up. 2. Dilation by a factor of 1.5. 3. Reflection across the x-axis. 4. 90° rotation, clockwise.