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  • Terminology

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  • Definition of augmented matrix (of a linear system)
  • Definition of coefficient matrix of a linear system
  • Definition of constant vector of a linear system
  • Definition of solution vector of a linear system
  • Definition of matrix representation of a linear system
  • Definition of domain of a linear transformation
  • Definition of codomain of a linear transformation
  • Definition of image (of a point) under a linear transformation
  • Definition of pre-image (of a point) under a linear transformation
  • Definition of onto/surjective linear transformation
  • Definition of one-to-one/injective linear transformation
  • Definition of range of linear transformation
  • Definition of kernel of linear transformation
  • Definition of invertible linear transformation
  • Definition of inverse of a linear transformation
  • Non-example of a linear transformation
  • Definition of linear transformation/homomorphism
  • Definition of identity linear transformation
  • Definition of sum of linear transformations
  • The sum of linear transformations is a linear transformation
  • Definition of scalar multiple of a linear transformation
  • A scalar multiple of a linear transformation is a linear transformation
  • Definition of pre-image of linear transformation
  • Definition of range of a linear transformation
  • Definition of invertible/nonsingular linear transformation
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Description:Added range of linear transformation content
# Definition of range of linear transformation

Put content here**Definition:** The *range* (or *image*) of a linear transformation \(T: V \to W\) is the set of all possible output vectors:
\[\text{range}(T) = \text{im}(T) = \{T(\mathbf{v}) : \mathbf{v} \in V\} \subseteq W\]
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The range is always a subspace of the codomain \(W\).
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**Example:** For \(T: \mathbb{R}^3 \to \mathbb{R}^3\) defined by \(T(x,y,z) = (x,y,0)\), the range is the \(xy\)-plane: \(\{(x,y,0) : x,y \in \mathbb{R}\}\).
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**Example:** For \(T: \mathbb{R}^2 \to \mathbb{R}^2\) defined by \(T(x,y) = (x+y, 2x+2y)\), the range is the line spanned by \((1,2)\).
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**Dimension of the range:** The dimension of the range is called the *rank* of \(T\). For a matrix transformation \(T(\mathbf{x}) = A\mathbf{x}\), the rank equals the number of pivot columns (or the column rank of \(A\)).

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