Learn on PengiYoshiwara Intermediate AlgebraChapter 2: Applications of Linear Models

Lesson 4: Gaussian Reduction

New Concept Gaussian reduction is a systematic method for solving a $3 \times 3$ linear system. It uses linear combinations to transform the system into a simpler triangular form, which can then be solved efficiently using back substitution.

Section 1

πŸ“˜ Gaussian Reduction

New Concept

Gaussian reduction is a systematic method for solving a 3Γ—33 \times 3 linear system. It uses linear combinations to transform the system into a simpler triangular form, which can then be solved efficiently using back-substitution.

What’s next

Next, you'll master this method through interactive examples and practice problems, learning to solve for the unique intersection point of three planes.

Section 2

Solutions to 3x3 Systems

Property

A solution to an equation in three variables, such as x+2yβˆ’3z=βˆ’4x + 2y - 3z = -4 is an ordered triple of numbers that satisfies the equation.

A solution to a system of three linear equations in three variables is an ordered triple that satisfies each equation in the system.

An ordered triple (x,y,z)(x, y, z) can be represented geometrically as a point in space using a three-dimensional Cartesian coordinate system, as shown in the figure.

Section 3

Back-Substitution

Property

A special case is called back-substitution. It works when one of the equations involves exactly one variable, and a second equation involves that same variable and just one other variable. A 3Γ—33 \times 3 system with these properties is said to be in triangular form.

Examples

  • Solve the system: x+y+z=8x+y+z=8, yβˆ’z=1y-z=1, and 2z=42z=4. From the third equation, z=2z=2. Substitute into the second: yβˆ’2=1y-2=1, so y=3y=3. Substitute both into the first: x+3+2=8x+3+2=8, so x=3x=3. The solution is (3,3,2)(3, 3, 2).
  • Use back-substitution on the system 2xβˆ’y+z=52x-y+z=5, 3y+z=113y+z=11, and z=2z=2. Substitute z=2z=2 into the second equation to find 3y+2=113y+2=11, so y=3y=3. Substitute both values into the first: 2xβˆ’3+2=52x-3+2=5, so x=3x=3. The solution is (3,3,2)(3, 3, 2).

Section 4

Gaussian Reduction

Property

The method for solving a general 3Γ—33 \times 3 linear system is called Gaussian reduction. We use linear combinations to reduce the system to triangular form, and then use back-substitution to find the solutions.

Steps for Solving a 3Γ—33 \times 3 Linear System.

  1. Clear each equation of fractions and put it in standard form.
  2. Choose two of the equations and eliminate one of the variables by forming a linear combination.
  3. Choose a different pair of equations and eliminate the same variable.
  4. Form a 2Γ—22 \times 2 system with the equations found in steps (2) and (3). Eliminate one of the variables from this 2Γ—22 \times 2 system by using a linear combination.
  5. Form a triangular system by choosing among the previous equations. Use back-substitution to solve the triangular system.

Examples

  • To start solving x+y+z=2x+y+z=2 and 2xβˆ’y+z=12x-y+z=1, eliminate xx. Multiply the first equation by βˆ’2-2 to get βˆ’2xβˆ’2yβˆ’2z=βˆ’4-2x-2y-2z=-4. Add this to the second equation to get βˆ’3yβˆ’z=βˆ’3-3y-z=-3.

Section 5

Inconsistent and Dependent Systems

Property

If, at any step in forming linear combinations, we obtain an equation of the form

0x+0y+0z=k,(k≠0)0x + 0y + 0z = k, \quad (k \neq 0)

then the system is inconsistent and has no solution. If we don't obtain such an equation, but we do obtain one of the form

0x+0y+0z=00x + 0y + 0z = 0

then the system is dependent and has infinitely many solutions.

Examples

  • Consider the system x+y+z=5x+y+z=5 and x+y+z=1x+y+z=1. Subtracting the second from the first gives (x+y+z)βˆ’(x+y+z)=5βˆ’1(x+y+z)-(x+y+z) = 5-1, which results in 0=40=4. This contradiction means the system is inconsistent.
  • Consider the system 2xβˆ’y=32x-y=3 and 4xβˆ’2y=64x-2y=6. Multiply the first equation by βˆ’2-2 to get βˆ’4x+2y=βˆ’6-4x+2y=-6. Adding this to the second equation gives 0=00=0. This indicates the system is dependent.

Book overview

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

Continue this chapter

Chapter 2: Applications of Linear Models

  1. Lesson 1

    Lesson 1: Linear Regression

  2. Lesson 2

    Lesson 2: Linear Systems

  3. Lesson 3

    Lesson 3: Algebraic Solution of Systems

  4. Lesson 4Current

    Lesson 4: Gaussian Reduction

  5. Lesson 5

    Lesson 5: Linear Inequalities in Two Variables

  6. Lesson 6

    Lesson 6: Chapter Summary and Review

Lesson overview

Expand to review the lesson summary and core properties.

Expand

Section 1

πŸ“˜ Gaussian Reduction

New Concept

Gaussian reduction is a systematic method for solving a 3Γ—33 \times 3 linear system. It uses linear combinations to transform the system into a simpler triangular form, which can then be solved efficiently using back-substitution.

What’s next

Next, you'll master this method through interactive examples and practice problems, learning to solve for the unique intersection point of three planes.

Section 2

Solutions to 3x3 Systems

Property

A solution to an equation in three variables, such as x+2yβˆ’3z=βˆ’4x + 2y - 3z = -4 is an ordered triple of numbers that satisfies the equation.

A solution to a system of three linear equations in three variables is an ordered triple that satisfies each equation in the system.

An ordered triple (x,y,z)(x, y, z) can be represented geometrically as a point in space using a three-dimensional Cartesian coordinate system, as shown in the figure.

Section 3

Back-Substitution

Property

A special case is called back-substitution. It works when one of the equations involves exactly one variable, and a second equation involves that same variable and just one other variable. A 3Γ—33 \times 3 system with these properties is said to be in triangular form.

Examples

  • Solve the system: x+y+z=8x+y+z=8, yβˆ’z=1y-z=1, and 2z=42z=4. From the third equation, z=2z=2. Substitute into the second: yβˆ’2=1y-2=1, so y=3y=3. Substitute both into the first: x+3+2=8x+3+2=8, so x=3x=3. The solution is (3,3,2)(3, 3, 2).
  • Use back-substitution on the system 2xβˆ’y+z=52x-y+z=5, 3y+z=113y+z=11, and z=2z=2. Substitute z=2z=2 into the second equation to find 3y+2=113y+2=11, so y=3y=3. Substitute both values into the first: 2xβˆ’3+2=52x-3+2=5, so x=3x=3. The solution is (3,3,2)(3, 3, 2).

Section 4

Gaussian Reduction

Property

The method for solving a general 3Γ—33 \times 3 linear system is called Gaussian reduction. We use linear combinations to reduce the system to triangular form, and then use back-substitution to find the solutions.

Steps for Solving a 3Γ—33 \times 3 Linear System.

  1. Clear each equation of fractions and put it in standard form.
  2. Choose two of the equations and eliminate one of the variables by forming a linear combination.
  3. Choose a different pair of equations and eliminate the same variable.
  4. Form a 2Γ—22 \times 2 system with the equations found in steps (2) and (3). Eliminate one of the variables from this 2Γ—22 \times 2 system by using a linear combination.
  5. Form a triangular system by choosing among the previous equations. Use back-substitution to solve the triangular system.

Examples

  • To start solving x+y+z=2x+y+z=2 and 2xβˆ’y+z=12x-y+z=1, eliminate xx. Multiply the first equation by βˆ’2-2 to get βˆ’2xβˆ’2yβˆ’2z=βˆ’4-2x-2y-2z=-4. Add this to the second equation to get βˆ’3yβˆ’z=βˆ’3-3y-z=-3.

Section 5

Inconsistent and Dependent Systems

Property

If, at any step in forming linear combinations, we obtain an equation of the form

0x+0y+0z=k,(k≠0)0x + 0y + 0z = k, \quad (k \neq 0)

then the system is inconsistent and has no solution. If we don't obtain such an equation, but we do obtain one of the form

0x+0y+0z=00x + 0y + 0z = 0

then the system is dependent and has infinitely many solutions.

Examples

  • Consider the system x+y+z=5x+y+z=5 and x+y+z=1x+y+z=1. Subtracting the second from the first gives (x+y+z)βˆ’(x+y+z)=5βˆ’1(x+y+z)-(x+y+z) = 5-1, which results in 0=40=4. This contradiction means the system is inconsistent.
  • Consider the system 2xβˆ’y=32x-y=3 and 4xβˆ’2y=64x-2y=6. Multiply the first equation by βˆ’2-2 to get βˆ’4x+2y=βˆ’6-4x+2y=-6. Adding this to the second equation gives 0=00=0. This indicates the system is dependent.

Book overview

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

Continue this chapter

Chapter 2: Applications of Linear Models

  1. Lesson 1

    Lesson 1: Linear Regression

  2. Lesson 2

    Lesson 2: Linear Systems

  3. Lesson 3

    Lesson 3: Algebraic Solution of Systems

  4. Lesson 4Current

    Lesson 4: Gaussian Reduction

  5. Lesson 5

    Lesson 5: Linear Inequalities in Two Variables

  6. Lesson 6

    Lesson 6: Chapter Summary and Review