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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 Gaussian elimination method
# Parametric vector form of the solution set of a system of linear equations

Put content here**Definition:** **Gaussian elimination** is a systematic method for solving systems of linear equations by transforming the augmented matrix $[A | b]$ into echelon form using three types of **elementary row operations**:
⏎
1. **Swap** two rows: $R_i \leftrightarrow R_j$
2. **Scale** a row by a nonzero constant: $R_i \leftarrow c \cdot R_i$
3. **Replace** a row by itself plus a multiple of another: $R_i \leftarrow R_i + c \cdot R_j$
⏎
**Algorithm:**
1. Write the system as an augmented matrix
2. Use row operations to create zeros below each pivot (left to right, top to bottom)
3. The resulting echelon form reveals the solution by back-substitution
⏎
**Example:**
$$\begin{bmatrix} 2 & 1 & | & 5 \\ 1 & -3 & | & -1 \end{bmatrix} \xrightarrow{R_1 \leftrightarrow R_2} \begin{bmatrix} 1 & -3 & | & -1 \\ 2 & 1 & | & 5 \end{bmatrix} \xrightarrow{R_2 - 2R_1} \begin{bmatrix} 1 & -3 & | & -1 \\ 0 & 7 & | & 7 \end{bmatrix}$$
⏎
From the echelon form: $y = 1$, $x = -1 + 3(1) = 2$.

# Parents

* Linear systems of equations
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