# Row equivalent matrices represent equivalent linear systems

Put content here**Theorem: Row Equivalence and Equivalent Linear Systems**
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Two matrices are row equivalent if one can be obtained from the other by a sequence of elementary row operations. Row equivalent augmented matrices represent linear systems with identical solution sets.
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**Statement:** If two augmented matrices are row equivalent, then the corresponding linear systems have exactly the same solutions.
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**Elementary row operations:**
1. **Row replacement**: Add a multiple of one row to another
2. **Row scaling**: Multiply a row by a nonzero constant
3. **Row interchange**: Swap two rows
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**Why it works:** Each elementary row operation corresponds to an algebraically valid manipulation of equations:
- Row replacement = adding a multiple of one equation to another (does not change solutions)
- Row scaling = multiplying both sides of an equation by a nonzero constant
- Row interchange = reordering equations
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**Application:** This theorem justifies Gaussian elimination. We transform the augmented matrix `[A | b]` to a simpler row-equivalent form (echelon or reduced echelon form) and read off the solution from the simpler system, knowing it is the same as the original.

# Parents

* Linear systems and matrices