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  • Linear systems of equations

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  • Basic terminology
  • Parametric form of the solution set of a system of linear equations
  • Parametric vector form of the solution set of a system of linear equations
  • Gaussian elimination as a method to solve a linear system
  • Definition of echelon form of a linear system
  • All echelon forms of a linear system have the same free variables
  • Definition of equation operations on a linear system
  • Equation operations on a linear system give an equivalent system.
  • Definition of equivalent systems of linear equations
  • The geometry of linear systems
  • Definition of consistent linear system
  • Definition of inconsistent linear system
  • Definition of homogeneous linear system of equations
  • Homogeneous linear systems are consistent.
  • Definition of nontrivial solution to a homogeneous linear system of equations
  • Definition of trivial solution to a homogeneous linear system of equations
  • A homogeneous system has a nontrivial solution if and only if it has a free variable.
  • The number of solutions to a linear system
  • Definition of basic/dependent/leading variable in a linear system
  • Definition of free/independent variable in a linear system
  • Theorem describing the vector form of sulutions to a linear system.
  • The solutions to a nonhomogeneous system are given by a particular solution plus the solutions to the homogeneous system.
  • Definition of ill-conditioned linear system
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Description:Added theorem about equation operations preserving equivalence
# Definition of equation operations on a linear system

Put content here**Theorem:** Applying any of the three equation operations to a linear system produces a new system that is **equivalent** to the original — i.e., both systems have exactly the same solution set.
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**Proof sketch:** Each operation is reversible:
- Swapping equations can be undone by swapping them back
- Scaling by $c \neq 0$ can be undone by scaling by $1/c$
- Replacing $E_i$ with $E_i + cE_j$ can be undone by replacing with $E_i - cE_j$
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Since each operation is invertible, no solutions are lost or gained.
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**Why this matters:** This theorem justifies Gaussian elimination. We can transform a system into a simpler equivalent form (echelon form) and solve that instead of the original system.

# Parents

* Linear systems of equations
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