Proving row space column space

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SUMMARY

The discussion centers on proving that the row space of matrix A equals its column space, given the equation AB = AT, where A and B are n x n matrices. The key argument presented is that each column of the product AB can be expressed as a linear combination of the columns of A, specifically through the multiplication of A with the corresponding columns of B. This establishes that the column space of A is contained within its row space, thereby proving the equality of the two spaces.

PREREQUISITES
  • Understanding of linear algebra concepts, specifically row space and column space.
  • Familiarity with matrix multiplication and properties of transposes.
  • Knowledge of linear combinations and vector spaces.
  • Basic proficiency in working with n x n matrices.
NEXT STEPS
  • Study the properties of matrix transposes and their implications on row and column spaces.
  • Learn about the Rank-Nullity Theorem and its relevance to row and column spaces.
  • Explore examples of proving relationships between row space and column space in various matrices.
  • Investigate the implications of linear transformations on row and column spaces.
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This discussion is beneficial for students and professionals in mathematics, particularly those studying linear algebra, as well as educators teaching matrix theory and vector spaces.

nhrock3
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A , B are nXn matrices
and
AB=(A)^t
t-is transpose
prove that the space spanned by A's row equals the space spanned by A's columns
i know that there dimentions are equals
so in order to prove equality i need to prove that one is a part of the other
how to do it?

each column i of (AB)_i=A*B_i
i was told by my proff that that column i of AB is a member from the span of the columns of A

but i don't get this result
suppose the member of B_i column is (c1,c2,..,cn)
so the multiplication of A by the B_i column
we get then the first member is dot product from the first row with (c1,c2,..,cn)
i can't see how its a variation from the A columns?
 
Last edited:
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yeah i think you're on the right track,
A.B = A^T

now consider a the kth column B, the vector B_k, which when multiplied with A yields the kth column of A_T, (A^T)_k
A.B_k = (A^T)_k

so the kth column of A^T is a linear combination of the columns of A, given by the components of B_k.
 

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