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Questions and Answers
What is the primary purpose of Gaussian elimination in solving systems of linear equations?
What is the primary purpose of Gaussian elimination in solving systems of linear equations?
In row echelon form, where should each leading 1 of the matrix lie?
In row echelon form, where should each leading 1 of the matrix lie?
What is a characteristic of a row that allows it to be moved below any other row without altering the solution?
What is a characteristic of a row that allows it to be moved below any other row without altering the solution?
For Gaussian elimination, what must a zero row be able to precede in a matrix?
For Gaussian elimination, what must a zero row be able to precede in a matrix?
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What kind of elements should be present in the final column of a matrix in desired row echelon form?
What kind of elements should be present in the final column of a matrix in desired row echelon form?
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What role does the augmented matrix play in solving linear equations with Gaussian elimination?
What role does the augmented matrix play in solving linear equations with Gaussian elimination?
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What happens to a row that has all entries as zero except for a single leading 1 when using Gaussian elimination?
What happens to a row that has all entries as zero except for a single leading 1 when using Gaussian elimination?
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In the context of Gaussian elimination, what does 'x' represent in the augmented matrix 'Ax = b'?
In the context of Gaussian elimination, what does 'x' represent in the augmented matrix 'Ax = b'?
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How does Gaussian elimination help simplify solving systems of linear equations?
How does Gaussian elimination help simplify solving systems of linear equations?
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What transformation occurs to an augmented matrix during Gaussian elimination?
What transformation occurs to an augmented matrix during Gaussian elimination?
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Study Notes
Systems of Equations
Gaussian elimination is a method used to solve systems of linear equations. It involves manipulating the given system into row echelon form. This process can be performed either by hand or with the help of a computer.
Row Echelon Form
The first step in using Gaussian elimination is finding the row echelon form of a matrix. A matrix is said to be in row echelon form if it satisfies these conditions:
- Each leading 1 of the matrix must lie directly above another leading 1 of the matrix.
- If any row has all entries zero except possibly for a single leading 1, then this row may be moved below any other row without changing the solution of the system.
- Any zero row may precede any nonzero row.
For example, consider the matrix A:
1 1 | -5 8
2 3 | 7 10
4 6 | 15 19
By performing Gaussian elimination, we can transform A into its row echelon form:
1 1 | 0 -3
0 0 | 0 0
0 0 | 0 0
Solving Linear Equations Using Row Reduction
To solve a system of linear equations using Gaussian elimination, follow these steps:
- Write the system you want to solve in augmented matrix form
Ax = b, whereArepresents the coefficient matrix,xrepresents the unknown variables, andbrepresents the constant term. - Perform row operations until the augmented matrices are transformed into row echelon form.
- When you reach the desired row echelon form, the final column will have only two unique elements: zeros and ones. These elements represent the solution(s) to the original system of linear equations.
Example Problem
Consider the following system of equations:
2x + 3y = 7
x - y = -2
We can rewrite this system as an augmented matrix:
2 3 | 7
1 -1 | -2
Now perform Gaussian elimination to find the row echelon form:
2 3 | 7
0 0 | 0
0 0 | 0
From the last column, we see that there are multiple solutions:
x = 7
y = 2
This means that there are infinitely many pairs (x, y) that satisfy the given equation. For example, (7, 2) and (14, 4) are both valid solutions.
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Description
Learn about Gaussian elimination, a method used to solve systems of linear equations by transforming matrices into row echelon form. Discover how to use row reduction to find unique solutions or infinite solutions to a system of equations.
