Table of contents
- 0. Review of Algebra4h 16m
- 1. Equations & Inequalities3h 18m
- 2. Graphs of Equations43m
- 3. Functions2h 17m
- 4. Polynomial Functions1h 44m
- 5. Rational Functions1h 23m
- 6. Exponential & Logarithmic Functions2h 28m
- 7. Systems of Equations & Matrices4h 6m
- 8. Conic Sections2h 23m
- 9. Sequences, Series, & Induction1h 19m
- 10. Combinatorics & Probability1h 45m
7. Systems of Equations & Matrices
Introduction to Matrices
6:57 minutes
Problem 10c
Textbook Question
In Exercises 8–11, use Gaussian elimination to find the complete solution to each system, or show that none exists.
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1
<Step 1: Write the system of equations in augmented matrix form.>
<Step 2: Use row operations to get a leading 1 in the first row, first column.>
<Step 3: Eliminate the entries below the leading 1 in the first column by using row operations.>
<Step 4: Move to the second row, second column, and repeat the process to get a leading 1 and eliminate entries below it.>
<Step 5: Continue this process for each column until the matrix is in row-echelon form, then back-substitute to find the solution.>
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Gaussian Elimination
Gaussian elimination is a method for solving systems of linear equations. It involves transforming the system's augmented matrix into row echelon form using a series of row operations, which include swapping rows, multiplying a row by a non-zero scalar, and adding or subtracting rows. This process simplifies the system, making it easier to find solutions or determine if no solution exists.
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Row Echelon Form
Row echelon form is a specific arrangement of a matrix where all non-zero rows are above any rows of all zeros, and the leading coefficient of each non-zero row (the first non-zero number from the left) is to the right of the leading coefficient of the previous row. This structure is crucial for identifying the number of solutions in a system of equations, as it helps in back substitution to find the values of the variables.
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Consistency of a System
A system of linear equations is considered consistent if it has at least one solution, and inconsistent if it has no solutions. During Gaussian elimination, if a row reduces to a form that implies a contradiction (such as 0 = 1), the system is inconsistent. Understanding the consistency of a system is essential for determining whether to expect a unique solution, infinitely many solutions, or none at all.
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