Linear Algebra - Spans and Linear Independence

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Homework Help Overview

The discussion revolves around linear transformations between vector spaces, specifically focusing on examples that illustrate concepts of linear independence and spanning sets. The original poster seeks to provide examples of linear transformations where the properties of the vectors in the domain do not correspond to those in the codomain.

Discussion Character

  • Conceptual clarification, Problem interpretation, Assumption checking

Approaches and Questions Raised

  • Participants explore the implications of linear independence and spanning sets in the context of linear transformations. There are attempts to clarify the requirements for the vectors a(1),..., a(n) in relation to the transformations T.

Discussion Status

Some participants have provided feedback on the original poster's matrices, emphasizing the importance of including the vectors a(i). There is ongoing clarification regarding the conditions under which the examples should be constructed, and the original poster expresses confusion about the requirements for a(1),..., a(n).

Contextual Notes

Participants note the dimensional constraints of the vector spaces involved, particularly the implications of mapping from a higher-dimensional space to a lower-dimensional one, which affects the linear independence of the vectors in the range.

sassie
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Homework Statement



Let A and B be vector spaces, T:A->B be a linear transformation.

Give examples of:

(a) T, where a(1),... a(n) are linearly independent vectors in A, but T(a(1)),...T(a(n)) are not.
(b) T, where T(a(1)),...T(a(n)) span the range of T, but a(1),... a(n) do not span A.

Homework Equations



My ideas were to think about onto and 1-to-1-ness. (e.g. T is 1-to-1 iff the columns of the standard associated matrix T are linearly independent). However, I'm not 100% sure because the equations I have don't really make sure, and I'm not sure whether they apply to vector spaces.

The Attempt at a Solution



Let T be:

(a) [1 2 4 0
2 0 2 0
3 1 1 0]

(b) [1 2 3
0 2 5
0 0 2
0 0 0]
 
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Those are good matrices, but don't forget the a(i)'s.
 
So my thinking is correct?

Sorry, but what do you mean by "a(i)'s"?

Cheers.
 
sassie said:
So my thinking is correct?

Sorry, but what do you mean by "a(i)'s"?

Cheers.

Yep. It asks for a(1),...,a(n) that satisfy those requirements.
 
Okay, so it my answer to (a) correct because it contains the zero vector? If not, how do I go about doing it?
This was the part of the question I was most confused about. I get the onto and 1-to-1 part for T not being linear independence and T spanning the range of T, but I don't get the a(1)...a(n) part. Can you help me on that part?
 
sassie said:
Okay, so it my answer to (a) correct because it contains the zero vector? If not, how do I go about doing it?
This was the part of the question I was most confused about. I get the onto and 1-to-1 part for T not being linear independence and T spanning the range of T, but I don't get the a(1)...a(n) part. Can you help me on that part?

Your answer to (a) is correct because it is a linear map from a 4-dimensional space to a 3-dimensional space. It is trivial that there do not exist 4 linearly independent vectors in a 3-dimensional space. You thus need only show 4 linearly independent vectors in the domain, knowing that they cannot possibly be mapped to 4 linearly independent vectors in the range.
 
And how would I do that? Do I need to take vectors out of the given matrix, or do I need to make up new examples?
 

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