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  • Echelon matrices

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  • Example of putting a matrix in echelon form
  • Example of putting a matrix in echelon form and identifying the pivot columns
  • Definition of (echelon matrix/matrix in (row) echelon form)
  • Gauss-Jordan procedure to put a matrix into reduced row echelon form
  • Example of (echelon matrix/matrix in (row) echelon form)
  • Definition of (row) echelon form of a matrix
  • Definition of matrix in reduced row echelon form
  • Definition of reduced row echelon form of a matrix
  • Definition of row reduce a matrix
  • Example of row reducing a 3-by-3 matrix
  • Example of row reducing a 4-by-4 matrix
  • Every matrix is row-equivalent to a matrix in reduced row echelon form.
  • Every matrix is row-equivalent to only one matrix in reduced row echelon form.
  • Definition of extended reduced row echelon form of a matrix
  • Theorem describing properties of the block matrices of the extended reduced row echelon form of a matrix
  • Theorem describing spaces associated to the block matrices of the extended reduced row echelon form of a matrix
  • Theorem describing the dimension of spaces associated to the block matrices of the extended reduced row echelon form of a matrix
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Description:Added theorem
# Theorem describing spaces associated to the block matrices of the extended reduced row echelon form of a matrix

Put content here**Theorem:** The extended RREF $[R \mid E]$ of $A$ simultaneously reveals all four fundamental subspaces:
⏎
1. **Row space of $A$** = Row space of $R$ = span of the nonzero rows of $R$.
2. **Null space of $A$** = Null space of $R$, found by solving $Rx = 0$ using free variables.
3. **Column space of $A$** = span of the pivot columns of the original matrix $A$ (identified by pivot positions in $R$).
4. **Left null space of $A$** = span of the bottom $m - r$ rows of $E$.
⏎
**Significance:** This is the most efficient single computation for understanding the complete structure of a linear transformation. All four subspaces and their dimensions are obtained from one row reduction.

# Parents

* Echelon matrices
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