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Algebra and Trigonometry

11.5 Matrices and Matrix Operations

Algebra and Trigonometry11.5 Matrices and Matrix Operations
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  1. Preface
  2. 1 Prerequisites
    1. Introduction to Prerequisites
    2. 1.1 Real Numbers: Algebra Essentials
    3. 1.2 Exponents and Scientific Notation
    4. 1.3 Radicals and Rational Exponents
    5. 1.4 Polynomials
    6. 1.5 Factoring Polynomials
    7. 1.6 Rational Expressions
    8. Key Terms
    9. Key Equations
    10. Key Concepts
    11. Review Exercises
    12. Practice Test
  3. 2 Equations and Inequalities
    1. Introduction to Equations and Inequalities
    2. 2.1 The Rectangular Coordinate Systems and Graphs
    3. 2.2 Linear Equations in One Variable
    4. 2.3 Models and Applications
    5. 2.4 Complex Numbers
    6. 2.5 Quadratic Equations
    7. 2.6 Other Types of Equations
    8. 2.7 Linear Inequalities and Absolute Value Inequalities
    9. Key Terms
    10. Key Equations
    11. Key Concepts
    12. Review Exercises
    13. Practice Test
  4. 3 Functions
    1. Introduction to Functions
    2. 3.1 Functions and Function Notation
    3. 3.2 Domain and Range
    4. 3.3 Rates of Change and Behavior of Graphs
    5. 3.4 Composition of Functions
    6. 3.5 Transformation of Functions
    7. 3.6 Absolute Value Functions
    8. 3.7 Inverse Functions
    9. Key Terms
    10. Key Equations
    11. Key Concepts
    12. Review Exercises
    13. Practice Test
  5. 4 Linear Functions
    1. Introduction to Linear Functions
    2. 4.1 Linear Functions
    3. 4.2 Modeling with Linear Functions
    4. 4.3 Fitting Linear Models to Data
    5. Key Terms
    6. Key Concepts
    7. Review Exercises
    8. Practice Test
  6. 5 Polynomial and Rational Functions
    1. Introduction to Polynomial and Rational Functions
    2. 5.1 Quadratic Functions
    3. 5.2 Power Functions and Polynomial Functions
    4. 5.3 Graphs of Polynomial Functions
    5. 5.4 Dividing Polynomials
    6. 5.5 Zeros of Polynomial Functions
    7. 5.6 Rational Functions
    8. 5.7 Inverses and Radical Functions
    9. 5.8 Modeling Using Variation
    10. Key Terms
    11. Key Equations
    12. Key Concepts
    13. Review Exercises
    14. Practice Test
  7. 6 Exponential and Logarithmic Functions
    1. Introduction to Exponential and Logarithmic Functions
    2. 6.1 Exponential Functions
    3. 6.2 Graphs of Exponential Functions
    4. 6.3 Logarithmic Functions
    5. 6.4 Graphs of Logarithmic Functions
    6. 6.5 Logarithmic Properties
    7. 6.6 Exponential and Logarithmic Equations
    8. 6.7 Exponential and Logarithmic Models
    9. 6.8 Fitting Exponential Models to Data
    10. Key Terms
    11. Key Equations
    12. Key Concepts
    13. Review Exercises
    14. Practice Test
  8. 7 The Unit Circle: Sine and Cosine Functions
    1. Introduction to The Unit Circle: Sine and Cosine Functions
    2. 7.1 Angles
    3. 7.2 Right Triangle Trigonometry
    4. 7.3 Unit Circle
    5. 7.4 The Other Trigonometric Functions
    6. Key Terms
    7. Key Equations
    8. Key Concepts
    9. Review Exercises
    10. Practice Test
  9. 8 Periodic Functions
    1. Introduction to Periodic Functions
    2. 8.1 Graphs of the Sine and Cosine Functions
    3. 8.2 Graphs of the Other Trigonometric Functions
    4. 8.3 Inverse Trigonometric Functions
    5. Key Terms
    6. Key Equations
    7. Key Concepts
    8. Review Exercises
    9. Practice Test
  10. 9 Trigonometric Identities and Equations
    1. Introduction to Trigonometric Identities and Equations
    2. 9.1 Solving Trigonometric Equations with Identities
    3. 9.2 Sum and Difference Identities
    4. 9.3 Double-Angle, Half-Angle, and Reduction Formulas
    5. 9.4 Sum-to-Product and Product-to-Sum Formulas
    6. 9.5 Solving Trigonometric Equations
    7. Key Terms
    8. Key Equations
    9. Key Concepts
    10. Review Exercises
    11. Practice Test
  11. 10 Further Applications of Trigonometry
    1. Introduction to Further Applications of Trigonometry
    2. 10.1 Non-right Triangles: Law of Sines
    3. 10.2 Non-right Triangles: Law of Cosines
    4. 10.3 Polar Coordinates
    5. 10.4 Polar Coordinates: Graphs
    6. 10.5 Polar Form of Complex Numbers
    7. 10.6 Parametric Equations
    8. 10.7 Parametric Equations: Graphs
    9. 10.8 Vectors
    10. Key Terms
    11. Key Equations
    12. Key Concepts
    13. Review Exercises
    14. Practice Test
  12. 11 Systems of Equations and Inequalities
    1. Introduction to Systems of Equations and Inequalities
    2. 11.1 Systems of Linear Equations: Two Variables
    3. 11.2 Systems of Linear Equations: Three Variables
    4. 11.3 Systems of Nonlinear Equations and Inequalities: Two Variables
    5. 11.4 Partial Fractions
    6. 11.5 Matrices and Matrix Operations
    7. 11.6 Solving Systems with Gaussian Elimination
    8. 11.7 Solving Systems with Inverses
    9. 11.8 Solving Systems with Cramer's Rule
    10. Key Terms
    11. Key Equations
    12. Key Concepts
    13. Review Exercises
    14. Practice Test
  13. 12 Analytic Geometry
    1. Introduction to Analytic Geometry
    2. 12.1 The Ellipse
    3. 12.2 The Hyperbola
    4. 12.3 The Parabola
    5. 12.4 Rotation of Axes
    6. 12.5 Conic Sections in Polar Coordinates
    7. Key Terms
    8. Key Equations
    9. Key Concepts
    10. Review Exercises
    11. Practice Test
  14. 13 Sequences, Probability, and Counting Theory
    1. Introduction to Sequences, Probability and Counting Theory
    2. 13.1 Sequences and Their Notations
    3. 13.2 Arithmetic Sequences
    4. 13.3 Geometric Sequences
    5. 13.4 Series and Their Notations
    6. 13.5 Counting Principles
    7. 13.6 Binomial Theorem
    8. 13.7 Probability
    9. Key Terms
    10. Key Equations
    11. Key Concepts
    12. Review Exercises
    13. Practice Test
  15. A | Proofs, Identities, and Toolkit Functions
  16. Answer Key
    1. Chapter 1
    2. Chapter 2
    3. Chapter 3
    4. Chapter 4
    5. Chapter 5
    6. Chapter 6
    7. Chapter 7
    8. Chapter 8
    9. Chapter 9
    10. Chapter 10
    11. Chapter 11
    12. Chapter 12
    13. Chapter 13
  17. Index

Learning Objectives

In this section, you will:
  • Find the sum and difference of two matrices.
  • Find scalar multiples of a matrix.
  • Find the product of two matrices.
Figure 1 (credit: “SD Dirk,” Flickr)

Two club soccer teams, the Wildcats and the Mud Cats, are hoping to obtain new equipment for an upcoming season. Table 1 shows the needs of both teams.

Wildcats Mud Cats
Goals 6 10
Balls 30 24
Jerseys 14 20
Table 1

A goal costs $300; a ball costs $10; and a jersey costs $30. How can we find the total cost for the equipment needed for each team? In this section, we discover a method in which the data in the soccer equipment table can be displayed and used for calculating other information. Then, we will be able to calculate the cost of the equipment.

Finding the Sum and Difference of Two Matrices

To solve a problem like the one described for the soccer teams, we can use a matrix, which is a rectangular array of numbers. A row in a matrix is a set of numbers that are aligned horizontally. A column in a matrix is a set of numbers that are aligned vertically. Each number is an entry, sometimes called an element, of the matrix. Matrices (plural) are enclosed in [ ] or ( ), and are usually named with capital letters. For example, three matrices named A,B, A,B, and C C are shown below.

A=[ 1 2 3 4 ],B=[ 1 2 7 0 −5 6 7 8 2 ],C=[ −1 0 3 3 2 1 ] A=[ 1 2 3 4 ],B=[ 1 2 7 0 −5 6 7 8 2 ],C=[ −1 0 3 3 2 1 ]

Describing Matrices

A matrix is often referred to by its size or dimensions:  m × n   m × n  indicating m m rows and n n columns. Matrix entries are defined first by row and then by column. For example, to locate the entry in matrix A A identified as a ij , a ij , we look for the entry in row i, i, column j. j. In matrix A,   A,   shown below, the entry in row 2, column 3 is a 23 . a 23 .

A=[ a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 ] A=[ a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 ]

A square matrix is a matrix with dimensions  n × n,  n × n, meaning that it has the same number of rows as columns. The 3×3 3×3 matrix above is an example of a square matrix.

A row matrix is a matrix consisting of one row with dimensions 1 × n. 1 × n.

[ a 11 a 12 a 13 ] [ a 11 a 12 a 13 ]

A column matrix is a matrix consisting of one column with dimensions m × 1. m × 1.

[ a 11 a 21 a 31 ] [ a 11 a 21 a 31 ]

A matrix may be used to represent a system of equations. In these cases, the numbers represent the coefficients of the variables in the system. Matrices often make solving systems of equations easier because they are not encumbered with variables. We will investigate this idea further in the next section, but first we will look at basic matrix operations.

Matrices

A matrix is a rectangular array of numbers that is usually named by a capital letter: A,B,C, A,B,C, and so on. Each entry in a matrix is referred to as a ij , a ij , such that i i represents the row and j j represents the column. Matrices are often referred to by their dimensions: m×n m×n indicating m m rows and n n columns.

Example 1

Finding the Dimensions of the Given Matrix and Locating Entries

Given matrix A: A:

  1. What are the dimensions of matrix A? A?
  2. What are the entries at a 31 a 31 and a 22 ? a 22 ?
    A=[ 2 1 0 2 4 7 3 1 2 ] A=[ 2 1 0 2 4 7 3 1 2 ]

Adding and Subtracting Matrices

We use matrices to list data or to represent systems. Because the entries are numbers, we can perform operations on matrices. We add or subtract matrices by adding or subtracting corresponding entries.

In order to do this, the entries must correspond. Therefore, addition and subtraction of matrices is only possible when the matrices have the same dimensions. We can add or subtract a  3 × 3   3 × 3  matrix and another  3 × 3   3 × 3  matrix, but we cannot add or subtract a  2 × 3   2 × 3  matrix and a  3 × 3   3 × 3  matrix because some entries in one matrix will not have a corresponding entry in the other matrix.

Adding and Subtracting Matrices

Given matrices A A and B B of like dimensions, addition and subtraction of A A and B B will produce matrix C C or
matrix D D of the same dimension.

A+B=C such that  a ij + b ij = c ij A+B=C such that  a ij + b ij = c ij
AB=D such that  a ij b ij = d ij AB=D such that  a ij b ij = d ij

Matrix addition is commutative.

A+B=B+A A+B=B+A

It is also associative.

( A+B )+C=A+( B+C ) ( A+B )+C=A+( B+C )

Example 2

Finding the Sum of Matrices

Find the sum of A A and B, B, given

A=[ a b c d ]   and  B=[ e f g h ] A=[ a b c d ]   and  B=[ e f g h ]

Example 3

Adding Matrix A and Matrix B

Find the sum of A A and B. B.

A=[ 4 1 3 2 ]  and  B=[ 5 9 0 7 ] A=[ 4 1 3 2 ]  and  B=[ 5 9 0 7 ]

Example 4

Finding the Difference of Two Matrices

Find the difference of A A and B. B.

A=[ −2 3 0 1 ]  and  B=[ 8 1 5 4 ] A=[ −2 3 0 1 ]  and  B=[ 8 1 5 4 ]

Example 5

Finding the Sum and Difference of Two 3 x 3 Matrices

Given A A and B: B:

  1. Find the sum.
  2. Find the difference.
A=[ 2 −10 −2 14 12 10 4 −2 2 ] and B=[ 6 10 −2 0 −12 −4 −5 2 −2 ] A=[ 2 −10 −2 14 12 10 4 −2 2 ] and B=[ 6 10 −2 0 −12 −4 −5 2 −2 ]

Try It #1

Add matrix A A and matrix B. B.

A=[ 2 6 1 0 1 −3 ]  and  B=[ 3 −2 1 5 −4 3 ] A=[ 2 6 1 0 1 −3 ]  and  B=[ 3 −2 1 5 −4 3 ]

Finding Scalar Multiples of a Matrix

Besides adding and subtracting whole matrices, there are many situations in which we need to multiply a matrix by a constant called a scalar. Recall that a scalar is a real number quantity that has magnitude, but not direction. For example, time, temperature, and distance are scalar quantities. The process of scalar multiplication involves multiplying each entry in a matrix by a scalar. A scalar multiple is any entry of a matrix that results from scalar multiplication.

Consider a real-world scenario in which a university needs to add to its inventory of computers, computer tables, and chairs in two of the campus labs due to increased enrollment. They estimate that 15% more equipment is needed in both labs. The school’s current inventory is displayed in Table 2.

Lab A Lab B
Computers 15 27
Computer Tables 16 34
Chairs 16 34
Table 2

Converting the data to a matrix, we have

C 2013 =[ 15 16 16 27 34 34 ] C 2013 =[ 15 16 16 27 34 34 ]

To calculate how much computer equipment will be needed, we multiply all entries in matrix C C by 0.15.

(0.15) C 2013 =[ (0.15)15 (0.15)16 (0.15)16 (0.15)27 (0.15)34 (0.15)34 ]=[ 2.25 2.4 2.4 4.05 5.1 5.1 ] (0.15) C 2013 =[ (0.15)15 (0.15)16 (0.15)16 (0.15)27 (0.15)34 (0.15)34 ]=[ 2.25 2.4 2.4 4.05 5.1 5.1 ]

We must round up to the next integer, so the amount of new equipment needed is

[ 3 3 3 5 6 6 ] [ 3 3 3 5 6 6 ]

Adding the two matrices as shown below, we see the new inventory amounts.

[ 15 16 16 27 34 34 ]+[ 3 3 3 5 6 6 ]=[ 18 19 19 32 40 40 ] [ 15 16 16 27 34 34 ]+[ 3 3 3 5 6 6 ]=[ 18 19 19 32 40 40 ]

This means

C 2014 =[ 18 19 19 32 40 40 ] C 2014 =[ 18 19 19 32 40 40 ]

Thus, Lab A will have 18 computers, 19 computer tables, and 19 chairs; Lab B will have 32 computers, 40 computer tables, and 40 chairs.

Scalar Multiplication

Scalar multiplication involves finding the product of a constant by each entry in the matrix. Given

A=[ a 11 a 12 a 21 a 22 ] A=[ a 11 a 12 a 21 a 22 ]

the scalar multiple cA cA is

cA=c[ a 11 a 12 a 21 a 22 ]     =[ c a 11 c a 12 c a 21 c a 22 ] cA=c[ a 11 a 12 a 21 a 22 ]     =[ c a 11 c a 12 c a 21 c a 22 ]

Scalar multiplication is distributive. For the matrices A,B, A,B, and C C with scalars a a and b, b,

a(A+B)=aA+aB (a+b)A=aA+bA a(A+B)=aA+aB (a+b)A=aA+bA

Example 6

Multiplying the Matrix by a Scalar

Multiply matrix A A by the scalar 3.

A=[ 8 1 5 4 ] A=[ 8 1 5 4 ]
Try It #2

Given matrix B, B, find −2B −2B where

B=[ 4 1 3 2 ] B=[ 4 1 3 2 ]

Example 7

Finding the Sum of Scalar Multiples

Find the sum 3A+2B. 3A+2B.

A=[ 1 −2 0 0 −1 2 4 3 −6 ] and B=[ −1 2 1 0 −3 2 0 1 −4 ] A=[ 1 −2 0 0 −1 2 4 3 −6 ] and B=[ −1 2 1 0 −3 2 0 1 −4 ]

Finding the Product of Two Matrices

In addition to multiplying a matrix by a scalar, we can multiply two matrices. Finding the product of two matrices is only possible when the inner dimensions are the same, meaning that the number of columns of the first matrix is equal to the number of rows of the second matrix. If A A is an  m × r   m × r  matrix and B B is an  r × n   r × n  matrix, then the product matrix AB AB is an  m × n   m × n  matrix. For example, the product AB AB is possible because the number of columns in A A is the same as the number of rows in B. B. If the inner dimensions do not match, the product is not defined.

We multiply entries of A A with entries of B B according to a specific pattern as outlined below. The process of matrix multiplication becomes clearer when working a problem with real numbers.

To obtain the entries in row i i of AB, AB, we multiply the entries in row i i of A A by column j j in B B and add. For example, given matrices A A and B, B, where the dimensions of A A are 2 × 3 2 × 3 and the dimensions of B B are 3 × 3, 3 × 3, the product of AB AB will be a 2 × 3 2 × 3 matrix.

A=[ a 11 a 12 a 13 a 21 a 22 a 23 ] and B=[ b 11 b 12 b 13 b 21 b 22 b 23 b 31 b 32 b 33 ] A=[ a 11 a 12 a 13 a 21 a 22 a 23 ] and B=[ b 11 b 12 b 13 b 21 b 22 b 23 b 31 b 32 b 33 ]

Multiply and add as follows to obtain the first entry of the product matrix AB. AB.

  1. To obtain the entry in row 1, column 1 of AB, AB, multiply the first row in A A by the first column in B, B, and add.
    [ a 11 a 12 a 13 ][ b 11 b 21 b 31 ]= a 11 b 11 + a 12 b 21 + a 13 b 31 [ a 11 a 12 a 13 ][ b 11 b 21 b 31 ]= a 11 b 11 + a 12 b 21 + a 13 b 31
  2. To obtain the entry in row 1, column 2 of AB, AB, multiply the first row of A A by the second column in B, B, and add.
    [ a 11 a 12 a 13 ][ b 12 b 22 b 32 ]= a 11 b 12 + a 12 b 22 + a 13 b 32 [ a 11 a 12 a 13 ][ b 12 b 22 b 32 ]= a 11 b 12 + a 12 b 22 + a 13 b 32
  3. To obtain the entry in row 1, column 3 of AB, AB, multiply the first row of A A by the third column in B, B, and add.
    [ a 11 a 12 a 13 ][ b 13 b 23 b 33 ]= a 11 b 13 + a 12 b 23 + a 13 b 33 [ a 11 a 12 a 13 ][ b 13 b 23 b 33 ]= a 11 b 13 + a 12 b 23 + a 13 b 33

We proceed the same way to obtain the second row of AB. AB. In other words, row 2 of A A times column 1 of B; B; row 2 of A A times column 2 of B; B; row 2 of A A times column 3 of B. B. When complete, the product matrix will be

AB=[ a 11 b 11 + a 12 b 21 + a 13 b 31 a 21 b 11 + a 22 b 21 + a 23 b 31 a 11 b 12 + a 12 b 22 + a 13 b 32 a 21 b 12 + a 22 b 22 + a 23 b 32 a 11 b 13 + a 12 b 23 + a 13 b 33 a 21 b 13 + a 22 b 23 + a 23 b 33 ] AB=[ a 11 b 11 + a 12 b 21 + a 13 b 31 a 21 b 11 + a 22 b 21 + a 23 b 31 a 11 b 12 + a 12 b 22 + a 13 b 32 a 21 b 12 + a 22 b 22 + a 23 b 32 a 11 b 13 + a 12 b 23 + a 13 b 33 a 21 b 13 + a 22 b 23 + a 23 b 33 ]

Properties of Matrix Multiplication

For the matrices A,B, A,B, and C C the following properties hold.

  • Matrix multiplication is associative: ( AB )C=A( BC ). ( AB )C=A( BC ).
  • Matrix multiplication is distributive: C(A+B)=CA+CB, (A+B)C=AC+BC. C(A+B)=CA+CB, (A+B)C=AC+BC.

Note that matrix multiplication is not commutative.

Example 8

Multiplying Two Matrices

Multiply matrix A A and matrix B. B.

A=[ 1 2 3 4 ]  and  B=[ 5 6 7 8 ] A=[ 1 2 3 4 ]  and  B=[ 5 6 7 8 ]

Example 9

Multiplying Two Matrices

Given A A and B: B:

  1. Find AB. AB.
  2. Find BA. BA.
A=[ −1 2 3 4 0 5 ] and  B=[ 5 −4 2 −1 0 3 ] A=[ −1 2 3 4 0 5 ] and  B=[ 5 −4 2 −1 0 3 ]

Analysis

Notice that the products AB AB and BA BA are not equal.

AB=[ −7 10 30 11 ][ −9 10 10 4 −8 −12 10 4 21 ]=BA AB=[ −7 10 30 11 ][ −9 10 10 4 −8 −12 10 4 21 ]=BA

This illustrates the fact that matrix multiplication is not commutative.

Q&A

Is it possible for AB to be defined but not BA?

Yes, consider a matrix A with dimension 3×4 3×4 and matrix B with dimension 4×2. 4×2. For the product AB the inner dimensions are 4 and the product is defined, but for the product BA the inner dimensions are 2 and 3 so the product is undefined.

Example 10

Using Matrices in Real-World Problems

Let’s return to the problem presented at the opening of this section. We have Table 3, representing the equipment needs of two soccer teams.

Wildcats Mud Cats
Goals 6 10
Balls 30 24
Jerseys 14 20
Table 3

We are also given the prices of the equipment, as shown in Table 4.

Goal $300
Ball $10
Jersey $30
Table 4

We will convert the data to matrices. Thus, the equipment need matrix is written as

E=[ 6 30 14 10 24 20 ] E=[ 6 30 14 10 24 20 ]

The cost matrix is written as

C=[ 300 10 30 ] C=[ 300 10 30 ]

We perform matrix multiplication to obtain costs for the equipment.

CE=[ 300 10 30 ][ 6 10 30 24 14 20 ]      =[ 300(6)+10(30)+30(14) 300(10)+10(24)+30(20) ]      =[ 2,520 3,840 ] CE=[ 300 10 30 ][ 6 10 30 24 14 20 ]      =[ 300(6)+10(30)+30(14) 300(10)+10(24)+30(20) ]      =[ 2,520 3,840 ]

The total cost for equipment for the Wildcats is $2,520, and the total cost for equipment for the Mud Cats is $3,840.

How To

Given a matrix operation, evaluate using a calculator.

  1. Save each matrix as a matrix variable [ A ],[ B ],[ C ],... [ A ],[ B ],[ C ],...
  2. Enter the operation into the calculator, calling up each matrix variable as needed.
  3. If the operation is defined, the calculator will present the solution matrix; if the operation is undefined, it will display an error message.

Example 11

Using a Calculator to Perform Matrix Operations

Find ABC ABC given

A=[ −15 25 32 41 −7 −28 10 34 −2 ],B=[ 45 21 −37 −24 52 19 6 −48 −31 ],and C=[ −100 −89 −98 25 −56 74 −67 42 −75 ]. A=[ −15 25 32 41 −7 −28 10 34 −2 ],B=[ 45 21 −37 −24 52 19 6 −48 −31 ],and C=[ −100 −89 −98 25 −56 74 −67 42 −75 ].

Media

Access these online resources for additional instruction and practice with matrices and matrix operations.

11.5 Section Exercises

Verbal

1.

Can we add any two matrices together? If so, explain why; if not, explain why not and give an example of two matrices that cannot be added together.

2.

Can we multiply any column matrix by any row matrix? Explain why or why not.

3.

Can both the products AB AB and BA BA be defined? If so, explain how; if not, explain why.

4.

Can any two matrices of the same size be multiplied? If so, explain why, and if not, explain why not and give an example of two matrices of the same size that cannot be multiplied together.

5.

Does matrix multiplication commute? That is, does AB=BA? AB=BA? If so, prove why it does. If not, explain why it does not.

Algebraic

For the following exercises, use the matrices below and perform the matrix addition or subtraction. Indicate if the operation is undefined.

A=[ 1 3 0 7 ],B=[ 2 14 22 6 ],C=[ 1 5 8 92 12 6 ],D=[ 10 14 7 2 5 61 ],E=[ 6 12 14 5 ],F=[ 0 9 78 17 15 4 ] A=[ 1 3 0 7 ],B=[ 2 14 22 6 ],C=[ 1 5 8 92 12 6 ],D=[ 10 14 7 2 5 61 ],E=[ 6 12 14 5 ],F=[ 0 9 78 17 15 4 ]
6.

A+B A+B

7.

C+D C+D

8.

A+C A+C

9.

BE BE

10.

C+F C+F

11.

DB DB

For the following exercises, use the matrices below to perform scalar multiplication.

A=[ 4 6 13 12 ],B=[ 3 9 21 12 0 64 ],C=[ 16 3 7 18 90 5 3 29 ],D=[ 18 12 13 8 14 6 7 4 21 ] A=[ 4 6 13 12 ],B=[ 3 9 21 12 0 64 ],C=[ 16 3 7 18 90 5 3 29 ],D=[ 18 12 13 8 14 6 7 4 21 ]
12.

5A 5A

13.

3B 3B

14.

−2B −2B

15.

−4C −4C

16.

1 2 C 1 2 C

17.

100D 100D

For the following exercises, use the matrices below to perform matrix multiplication.

A=[ −1 5 3 2 ],B=[ 3 6 4 −8 0 12 ],C=[ 4 10 −2 6 5 9 ],D=[ 2 −3 12 9 3 1 0 8 −10 ] A=[ −1 5 3 2 ],B=[ 3 6 4 −8 0 12 ],C=[ 4 10 −2 6 5 9 ],D=[ 2 −3 12 9 3 1 0 8 −10 ]
18.

AB AB

19.

BC BC

20.

CA CA

21.

BD BD

22.

DC DC

23.

CB CB

For the following exercises, use the matrices below to perform the indicated operation if possible. If not possible, explain why the operation cannot be performed.

A=[ 2 −5 6 7 ],B=[ −9 6 −4 2 ],C=[ 0 9 7 1 ],D=[ −8 7 −5 4 3 2 0 9 2 ],E=[ 4 5 3 7 −6 −5 1 0 9 ] A=[ 2 −5 6 7 ],B=[ −9 6 −4 2 ],C=[ 0 9 7 1 ],D=[ −8 7 −5 4 3 2 0 9 2 ],E=[ 4 5 3 7 −6 −5 1 0 9 ]
24.

A+BC A+BC

25.

4A+5D 4A+5D

26.

2C+B 2C+B

27.

3D+4E 3D+4E

28.

C−0.5D C−0.5D

29.

100D−10E 100D−10E

For the following exercises, use the matrices below to perform the indicated operation if possible. If not possible, explain why the operation cannot be performed. (Hint: A 2 =AA A 2 =AA )

A=[ −10 20 5 25 ],B=[ 40 10 −20 30 ],C=[ −1 0 0 −1 1 0 ] A=[ −10 20 5 25 ],B=[ 40 10 −20 30 ],C=[ −1 0 0 −1 1 0 ]
30.

AB AB

31.

BA BA

32.

CA CA

33.

BC BC

34.

A 2 A 2

35.

B 2 B 2

36.

C 2 C 2

37.

B 2 A 2 B 2 A 2

38.

A 2 B 2 A 2 B 2

39.

(AB) 2 (AB) 2

40.

(BA) 2 (BA) 2

For the following exercises, use the matrices below to perform the indicated operation if possible. If not possible, explain why the operation cannot be performed. (Hint: A 2 =AA A 2 =AA )

A=[ 1 0 2 3 ],B=[ −2 3 4 −1 1 −5 ],C=[ 0.5 0.1 1 0.2 −0.5 0.3 ],D=[ 1 0 −1 −6 7 5 4 2 1 ] A=[ 1 0 2 3 ],B=[ −2 3 4 −1 1 −5 ],C=[ 0.5 0.1 1 0.2 −0.5 0.3 ],D=[ 1 0 −1 −6 7 5 4 2 1 ]
41.

AB AB

42.

BA BA

43.

BD BD

44.

DC DC

45.

D 2 D 2

46.

A 2 A 2

47.

D 3 D 3

48.

(AB)C (AB)C

49.

A(BC) A(BC)

Technology

For the following exercises, use the matrices below to perform the indicated operation if possible. If not possible, explain why the operation cannot be performed. Use a calculator to verify your solution.

A=[ −2 0 9 1 8 −3 0.5 4 5 ],B=[ 0.5 3 0 −4 1 6 8 7 2 ],C=[ 1 0 1 0 1 0 1 0 1 ] A=[ −2 0 9 1 8 −3 0.5 4 5 ],B=[ 0.5 3 0 −4 1 6 8 7 2 ],C=[ 1 0 1 0 1 0 1 0 1 ]
50.

AB AB

51.

BA BA

52.

CA CA

53.

BC BC

54.

ABC ABC

Extensions

For the following exercises, use the matrix below to perform the indicated operation on the given matrix.

B=[ 1 0 0 0 0 1 0 1 0 ] B=[ 1 0 0 0 0 1 0 1 0 ]
55.

B 2 B 2

56.

B 3 B 3

57.

B 4 B 4

58.

B 5 B 5

59.

Using the above questions, find a formula for B n . B n . Test the formula for B 201 B 201 and B 202 , B 202 , using a calculator.

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