Learn on PengiSaxon Algebra 2Chapter 4: Lessons 31-40, Investigation 4

Lesson 32: Solving Linear Systems with Matrix Inverses (Exploration: Exploring Matrix Inverses)

In this Grade 10 Saxon Algebra 2 lesson, students learn how to find and verify matrix inverses, use the determinant to identify singular matrices, and solve linear systems by setting up and solving matrix equations of the form AX = B using the multiplicative inverse of the coefficient matrix. The lesson covers the inverse formula for 2×2 matrices, the identity matrix, and the step-by-step process of left-multiplying both sides of a matrix equation by A⁻¹ to isolate the variable matrix.

Section 1

📘 Solving Linear Systems with Matrix Inverses

New Concept

Two matrices AA and BB are inverses of each other if AB=BA=IA \cdot B = B \cdot A = I.

What’s next

Next, you'll calculate the inverse of a matrix and use it as a powerful new tool to solve systems of linear equations.

Section 2

Multiplicative inverse of a square matrix

The inverse of a matrix AA, notated A1A^{-1}, is a special matrix where multiplying it by AA results in the identity matrix, II. For two square matrices AA and BB to be inverses of each other, their product must be the identity matrix, regardless of the order of multiplication: AB=BA=IA \cdot B = B \cdot A = I.

Are P=[3725]P = \begin{bmatrix} 3 & 7 \\ 2 & 5 \end{bmatrix} and Q=[5723]Q = \begin{bmatrix} 5 & -7 \\ -2 & 3 \end{bmatrix} inverses? Yes, because PQ=[1001]=IP \cdot Q = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = I.
Are R=[1123]R = \begin{bmatrix} 1 & 1 \\ 2 & 3 \end{bmatrix} and S=[3120]S = \begin{bmatrix} 3 & -1 \\ -2 & 0 \end{bmatrix} inverses? No, because RS=[1102]IR \cdot S = \begin{bmatrix} 1 & -1 \\ 0 & -2 \end{bmatrix} \neq I.

Think of it like a secret decoder ring! Multiplying a matrix by its inverse is like undoing a secret code, getting you back to the simple identity matrix, which is the matrix equivalent of the number 1. This 'undo' feature is super powerful for solving complex matrix equations, just like division undoes multiplication with regular numbers.

Section 3

Inverse of a 2 x 2 Matrix

If A=[abcd]A = \begin{bmatrix} a & b \\ c & d \end{bmatrix} and its determinant adcb0ad - cb \neq 0, then the inverse of AA is given by the formula:

A1=1adcb[dbca]A^{-1} = \frac{1}{ad - cb} \begin{bmatrix} d & -b \\ -c & a \end{bmatrix}

For T=[5242]T = \begin{bmatrix} 5 & 2 \\ -4 & -2 \end{bmatrix}, the determinant is (5)(2)(2)(4)=2(5)(-2) - (2)(-4) = -2. So, T1=12[2245]=[1122.5]T^{-1} = \frac{1}{-2} \begin{bmatrix} -2 & -2 \\ 4 & 5 \end{bmatrix} = \begin{bmatrix} 1 & 1 \\ -2 & -2.5 \end{bmatrix}.
For M=[1819]M = \begin{bmatrix} 1 & 8 \\ 1 & 9 \end{bmatrix}, the determinant is (1)(9)(8)(1)=1(1)(9) - (8)(1) = 1. So, M1=11[9811]=[9811]M^{-1} = \frac{1}{1} \begin{bmatrix} 9 & -8 \\ -1 & 1 \end{bmatrix} = \begin{bmatrix} 9 & -8 \\ -1 & 1 \end{bmatrix}.

Finding the inverse of a 2x2 matrix is like a magic trick with four simple steps! First, calculate the determinant—it can't be zero. Then, swap the top-left and bottom-right numbers. After that, change the signs of the other two numbers. Finally, divide the entire new matrix by the determinant you found earlier. Voila, you have the inverse!

Section 4

Singular matrix

An n×nn \times n matrix AA is called a singular matrix if it does not have an inverse. This situation occurs if and only if the determinant of the matrix is equal to zero. So, for a singular matrix AA, we have detA=0\det A = 0. A matrix must have a non-zero determinant for its inverse to exist.

Matrix Y=[3648]Y = \begin{bmatrix} 3 & 6 \\ 4 & 8 \end{bmatrix} is singular because its determinant is (3)(8)(6)(4)=2424=0(3)(8) - (6)(4) = 24 - 24 = 0. It has no inverse.
Matrix Z=[1111]Z = \begin{bmatrix} 1 & 1 \\ 1 & 1 \end{bmatrix} is singular because its determinant is (1)(1)(1)(1)=0(1)(1) - (1)(1) = 0. Therefore, Z1Z^{-1} does not exist.

A singular matrix is like a lock with no key! It's a special type of square matrix that has a determinant of zero. Because its determinant is zero, you can't complete the final step of the inverse formula—dividing by zero is a big no-no in math. So, a singular matrix is stuck without an inverse buddy forever.

Section 5

Using an Inverse to Solve a Matrix Equation

If a matrix AA has an inverse and the matrix equation AX=BAX = B has a solution, then the solution is X=A1BX = A^{-1}B. To solve, you must multiply both sides of the equation by A1A^{-1} from the left side: (A1)AX=(A1)B(A^{-1})AX = (A^{-1})B, which simplifies to X=A1BX = A^{-1}B.

To solve [5723]X=[10]\begin{bmatrix} 5 & -7 \\ -2 & 3 \end{bmatrix} X = \begin{bmatrix} 1 \\ 0 \end{bmatrix}, first find the inverse: A1=[3725]A^{-1} = \begin{bmatrix} 3 & 7 \\ 2 & 5 \end{bmatrix}.
Then, solve for XX by multiplying: X=A1B=[3725][10]=[32]X = A^{-1}B = \begin{bmatrix} 3 & 7 \\ 2 & 5 \end{bmatrix} \begin{bmatrix} 1 \\ 0 \end{bmatrix} = \begin{bmatrix} 3 \\ 2 \end{bmatrix}.
The system 2x+y=52x+y=5, 3x+2y=83x+2y=8 becomes AX=BAX=B, where A=[2132]A = \begin{bmatrix} 2 & 1 \\ 3 & 2 \end{bmatrix} and B=[58]B = \begin{bmatrix} 5 \\ 8 \end{bmatrix}.

Solving AX=BAX=B is like solving the simple equation 5x=105x=10. To get xx, you multiply by the inverse of 5, which is 1/51/5. Similarly, to get the matrix XX, you multiply matrix BB by the inverse of matrix AA. Just remember, matrix multiplication order matters, so you must multiply from the left side: X=A1BX = A^{-1}B.

Book overview

Jump across lessons in the current chapter without opening the full course modal.

Continue this chapter

Chapter 4: Lessons 31-40, Investigation 4

  1. Lesson 1

    Lesson 31: Multiplying and Dividing Rational Expressions

  2. Lesson 2Current

    Lesson 32: Solving Linear Systems with Matrix Inverses (Exploration: Exploring Matrix Inverses)

  3. Lesson 3

    Lesson 33: Applying Counting Principles

  4. Lesson 4

    Lesson 34: Graphing Linear Equations II

  5. Lesson 5

    Lesson 35: Solving Quadratic Equations I

  6. Lesson 6

    Lesson 36: Using Parallel and Perpendicular Lines

  7. Lesson 7

    Lesson 37: Adding and Subtracting Rational Expressions

  8. Lesson 8

    Lesson 38: Dividing Polynomials Using Long Division

  9. Lesson 9

    Lesson 39: Graphing Linear Inequalities in Two Variables

  10. Lesson 10

    Lesson 40: Simplifying Radical Expressions

  11. Lesson 11

    Investigation 4: Understanding Cryptography

Lesson overview

Expand to review the lesson summary and core properties.

Expand

Section 1

📘 Solving Linear Systems with Matrix Inverses

New Concept

Two matrices AA and BB are inverses of each other if AB=BA=IA \cdot B = B \cdot A = I.

What’s next

Next, you'll calculate the inverse of a matrix and use it as a powerful new tool to solve systems of linear equations.

Section 2

Multiplicative inverse of a square matrix

The inverse of a matrix AA, notated A1A^{-1}, is a special matrix where multiplying it by AA results in the identity matrix, II. For two square matrices AA and BB to be inverses of each other, their product must be the identity matrix, regardless of the order of multiplication: AB=BA=IA \cdot B = B \cdot A = I.

Are P=[3725]P = \begin{bmatrix} 3 & 7 \\ 2 & 5 \end{bmatrix} and Q=[5723]Q = \begin{bmatrix} 5 & -7 \\ -2 & 3 \end{bmatrix} inverses? Yes, because PQ=[1001]=IP \cdot Q = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = I.
Are R=[1123]R = \begin{bmatrix} 1 & 1 \\ 2 & 3 \end{bmatrix} and S=[3120]S = \begin{bmatrix} 3 & -1 \\ -2 & 0 \end{bmatrix} inverses? No, because RS=[1102]IR \cdot S = \begin{bmatrix} 1 & -1 \\ 0 & -2 \end{bmatrix} \neq I.

Think of it like a secret decoder ring! Multiplying a matrix by its inverse is like undoing a secret code, getting you back to the simple identity matrix, which is the matrix equivalent of the number 1. This 'undo' feature is super powerful for solving complex matrix equations, just like division undoes multiplication with regular numbers.

Section 3

Inverse of a 2 x 2 Matrix

If A=[abcd]A = \begin{bmatrix} a & b \\ c & d \end{bmatrix} and its determinant adcb0ad - cb \neq 0, then the inverse of AA is given by the formula:

A1=1adcb[dbca]A^{-1} = \frac{1}{ad - cb} \begin{bmatrix} d & -b \\ -c & a \end{bmatrix}

For T=[5242]T = \begin{bmatrix} 5 & 2 \\ -4 & -2 \end{bmatrix}, the determinant is (5)(2)(2)(4)=2(5)(-2) - (2)(-4) = -2. So, T1=12[2245]=[1122.5]T^{-1} = \frac{1}{-2} \begin{bmatrix} -2 & -2 \\ 4 & 5 \end{bmatrix} = \begin{bmatrix} 1 & 1 \\ -2 & -2.5 \end{bmatrix}.
For M=[1819]M = \begin{bmatrix} 1 & 8 \\ 1 & 9 \end{bmatrix}, the determinant is (1)(9)(8)(1)=1(1)(9) - (8)(1) = 1. So, M1=11[9811]=[9811]M^{-1} = \frac{1}{1} \begin{bmatrix} 9 & -8 \\ -1 & 1 \end{bmatrix} = \begin{bmatrix} 9 & -8 \\ -1 & 1 \end{bmatrix}.

Finding the inverse of a 2x2 matrix is like a magic trick with four simple steps! First, calculate the determinant—it can't be zero. Then, swap the top-left and bottom-right numbers. After that, change the signs of the other two numbers. Finally, divide the entire new matrix by the determinant you found earlier. Voila, you have the inverse!

Section 4

Singular matrix

An n×nn \times n matrix AA is called a singular matrix if it does not have an inverse. This situation occurs if and only if the determinant of the matrix is equal to zero. So, for a singular matrix AA, we have detA=0\det A = 0. A matrix must have a non-zero determinant for its inverse to exist.

Matrix Y=[3648]Y = \begin{bmatrix} 3 & 6 \\ 4 & 8 \end{bmatrix} is singular because its determinant is (3)(8)(6)(4)=2424=0(3)(8) - (6)(4) = 24 - 24 = 0. It has no inverse.
Matrix Z=[1111]Z = \begin{bmatrix} 1 & 1 \\ 1 & 1 \end{bmatrix} is singular because its determinant is (1)(1)(1)(1)=0(1)(1) - (1)(1) = 0. Therefore, Z1Z^{-1} does not exist.

A singular matrix is like a lock with no key! It's a special type of square matrix that has a determinant of zero. Because its determinant is zero, you can't complete the final step of the inverse formula—dividing by zero is a big no-no in math. So, a singular matrix is stuck without an inverse buddy forever.

Section 5

Using an Inverse to Solve a Matrix Equation

If a matrix AA has an inverse and the matrix equation AX=BAX = B has a solution, then the solution is X=A1BX = A^{-1}B. To solve, you must multiply both sides of the equation by A1A^{-1} from the left side: (A1)AX=(A1)B(A^{-1})AX = (A^{-1})B, which simplifies to X=A1BX = A^{-1}B.

To solve [5723]X=[10]\begin{bmatrix} 5 & -7 \\ -2 & 3 \end{bmatrix} X = \begin{bmatrix} 1 \\ 0 \end{bmatrix}, first find the inverse: A1=[3725]A^{-1} = \begin{bmatrix} 3 & 7 \\ 2 & 5 \end{bmatrix}.
Then, solve for XX by multiplying: X=A1B=[3725][10]=[32]X = A^{-1}B = \begin{bmatrix} 3 & 7 \\ 2 & 5 \end{bmatrix} \begin{bmatrix} 1 \\ 0 \end{bmatrix} = \begin{bmatrix} 3 \\ 2 \end{bmatrix}.
The system 2x+y=52x+y=5, 3x+2y=83x+2y=8 becomes AX=BAX=B, where A=[2132]A = \begin{bmatrix} 2 & 1 \\ 3 & 2 \end{bmatrix} and B=[58]B = \begin{bmatrix} 5 \\ 8 \end{bmatrix}.

Solving AX=BAX=B is like solving the simple equation 5x=105x=10. To get xx, you multiply by the inverse of 5, which is 1/51/5. Similarly, to get the matrix XX, you multiply matrix BB by the inverse of matrix AA. Just remember, matrix multiplication order matters, so you must multiply from the left side: X=A1BX = A^{-1}B.

Book overview

Jump across lessons in the current chapter without opening the full course modal.

Continue this chapter

Chapter 4: Lessons 31-40, Investigation 4

  1. Lesson 1

    Lesson 31: Multiplying and Dividing Rational Expressions

  2. Lesson 2Current

    Lesson 32: Solving Linear Systems with Matrix Inverses (Exploration: Exploring Matrix Inverses)

  3. Lesson 3

    Lesson 33: Applying Counting Principles

  4. Lesson 4

    Lesson 34: Graphing Linear Equations II

  5. Lesson 5

    Lesson 35: Solving Quadratic Equations I

  6. Lesson 6

    Lesson 36: Using Parallel and Perpendicular Lines

  7. Lesson 7

    Lesson 37: Adding and Subtracting Rational Expressions

  8. Lesson 8

    Lesson 38: Dividing Polynomials Using Long Division

  9. Lesson 9

    Lesson 39: Graphing Linear Inequalities in Two Variables

  10. Lesson 10

    Lesson 40: Simplifying Radical Expressions

  11. Lesson 11

    Investigation 4: Understanding Cryptography