Row space of a transformation matrix

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SUMMARY

The discussion focuses on the row space of a transformation matrix, specifically in the context of linear transformations. It establishes that the row space is a subspace of the domain of the transformation. An example is provided with the transformation T: R^3 → R^2, represented by the matrix A = [[1, 0, 0], [0, 1, 0]], which projects vectors onto the x-y plane. This illustrates the relationship between the row space and the geometric interpretation of linear transformations.

PREREQUISITES
  • Understanding of linear transformations
  • Familiarity with matrix representation of transformations
  • Knowledge of subspaces in vector spaces
  • Basic concepts of R^n spaces
NEXT STEPS
  • Study the properties of null space in linear transformations
  • Explore the concept of column space and its significance
  • Learn about the rank-nullity theorem in linear algebra
  • Investigate geometric interpretations of linear transformations in R^n
USEFUL FOR

Students of linear algebra, educators teaching matrix theory, and anyone interested in the geometric aspects of linear transformations.

GwtBc
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Homework Statement


We're given some linear transformations, and asked what the null space, column space and row space of the matrix representations tell us

Homework Equations

The Attempt at a Solution


I know what information the column space and null space contain, but what does the row space of a transformation matrix tell me?
 
GwtBc said:

Homework Statement


We're given some linear transformations, and asked what the null space, column space and row space of the matrix representations tell us

Homework Equations

The Attempt at a Solution


I know what information the column space and null space contain, but what does the row space of a transformation matrix tell me?
The row space is a subspace of the domain of the transformation.
Here's a simple example.
Let T be a linear transformation, ##T: R^3 \to R^2##, with T(x) = Ax, with x in R3 and A defined as
##A = \begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \end{bmatrix}##
The row space of A is a two-dimensional subspace of R3; namely, the x-y plane. This transformation projects a vector x onto the x-y plane.
 

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