Chapter 8: Problem 31
Solve each system of equations using matrices. Use Gaussian elimination with back-substitution or Gauss-Jordan elimination. $$\left\\{\begin{array}{cc} 3 a-b-4 c= & 3 \\ 2 a-b+2 c= & -8 \\ a+2 b-3 c= & 9 \end{array}\right.$$
Short Answer
Expert verified
The solution to this system of equations is \(a = 6\), \(b = 26/5\) and \(c = 0\).
Step by step solution
01
Transform Equations Into Augmented Matrix
An augmented matrix is a way to represent a system of linear equations. Including the coefficients of the variables and the constants. The given system\n\[\begin{align*} 3a - b - 4c &= 3, \ 2a - b + 2c &= -8, \ a + 2b - 3c &= 9 \end{align*}\n can be represented as the augmented matrix\n\[\begin{bmatrix} 3 & -1 & -4 & | & 3 \ 2 & -1 & 2 & | & -8 \ 1 & 2 & -3 & | & 9 \end{bmatrix}\n\]
02
Apply Gaussian Elimination or Gauss-Jordan Elimination
We can use Gauss-Jordan elimination. Row operations are performed until the left side of the augmented matrix is in row-reduced echelon form. This involves getting a 1 in the first row first column by switching the first and third row:\n\[\begin{bmatrix} 1 & 2 & -3 & | & 9 \ 2 & -1 & 2 & | & -8 \ 3 & -1 & -4 & | & 3 \end{bmatrix}\n\]\nProceed with the elimination by subtracting appropriate multiples of the first row from the others to get zeros under the leading 1, then get leading 1 on second row second column:\n\[\begin{bmatrix} 1 & 2 & -3 & | & 9 \ 0 & -5 & 8 & | & -26 \ 0 & -7 & 2 & | & -24 \end{bmatrix}\n\]\nSubtract 1.4 times the second row from the third to get zero in third row, second column:\n\[\begin{bmatrix} 1 & 0 & -5 & | & 6 \ 0 & 1 & -8/5 & | & 26/5 \ 0 & 0 & 2 & | & 0 \end{bmatrix}\n\]\nFinally, divide the last row by 2 for simplicity:\n\[\begin{bmatrix} 1 & 0 & -5 & | & 6 \ 0 & 1 & -8/5 & | & 26/5 \ 0 & 0 & 1 & | & 0 \end{bmatrix}\n\]
03
Convert Matrix Back to System of Equations
The simplified matrix represents the system of equations: \n\[a - 5c = 6, \n b - 8/5 c = 26/5, c = 0.\]
04
Solve for Variables
From the last equation, it is clear that \(c = 0\). Substituting \(c = 0\) in the first and second equations, we can solve for \(a\) and \(b\) to get \(a = 6\) and \(b = 26/5\), respectively.
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Gaussian Elimination
Gaussian elimination is a systematic method for solving systems of linear equations. It involves performing row operations on the augmented matrix of a system to simplify it into an upper triangular form, where you can then solve for the variables through back-substitution.
Here's the process summed up:
Here's the process summed up:
- Form the augmented matrix from the system of equations.
- Begin with the top-left element and make it a 1, called a leading 1.
- Use row operations to create zeros in the column below this leading 1.
- Move to the next row and repeat the process to form another leading 1, making sure to create zeros in the column below it.
- Continue until the left part of the matrix is in upper triangular form.
- Finally, perform back-substitution to solve for the variables.
Gauss-Jordan Elimination
Gauss-Jordan elimination extends the Gaussian elimination method to yield the row-reduced echelon form (RREF) of the augmented matrix. In Gauss-Jordan elimination, row operations are used not only to form a triangular matrix but to achieve RREF, enabling easy determination of the solution set.
Key steps include:
Key steps include:
- Follow the Gaussian elimination steps until you have the upper triangular form.
- Proceed to make the diagonal elements all 1s, if they aren't already.
- Eliminate the non-zero elements above each leading 1 to get zeros all above and below the leading 1s.
- After achieving RREF, the solution to the system can be read directly from the matrix.
Augmented Matrix
An augmented matrix is a compact representation of a system of linear equations, where each row corresponds to an equation and each column corresponds to a coefficient of the variables, with an additional column for the constants. It is structured as follows:
- The matrix is divided into two sections. The left side holds the coefficients of the variables.
- The right side (after the vertical bar) contains the constants from the right-hand side of the equations.
- The arrangement mirrors the system of equations in a single mathematical structure, enabling matrix operations.
Row-Reduced Echelon Form
Row-Reduced Echelon Form (RREF) is the final, simplified form of a matrix that we aim to achieve using either Gaussian or Gauss-Jordan elimination. An RREF matrix has the following characteristics:
- Each leading entry in a row is 1 (called a pivot).
- Each leading 1 is the only non-zero entry in its column.
- Rows with all zeros are at the bottom of the matrix.
- The leading 1s descend down and to the right across the matrix.