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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 the dimension of spaces associated to the block matrices of the extended reduced row echelon form of a matrix

Put content here**Theorem (Dimensions from extended RREF):** For an $m \times n$ matrix $A$ of rank $r$, the dimensions of the four fundamental subspaces are:
⏎
| Subspace | Dimension |
|---|---|
| Row space (of $A$) | $r$ |
| Null space (of $A$) | $n - r$ |
| Column space (of $A$) | $r$ |
| Left null space (of $A^T$) | $m - r$ |
⏎
**Rank-Nullity Theorem:** $\dim(\text{Row space}) + \dim(\text{Null space}) = n$, i.e., $r + (n - r) = n$.
⏎
**Dual statement:** $\dim(\text{Column space}) + \dim(\text{Left null space}) = m$, i.e., $r + (m - r) = m$.
⏎
**Geometric interpretation:** The rank $r$ is the dimension of the image of the linear transformation $T(x) = Ax$. The nullity $n - r$ is the dimension of the kernel.

# Parents

* Echelon matrices
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