Linear Algebra: A Basis for a Finite Dim VS

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Discussion Overview

The discussion revolves around the criteria for a set of vectors to be considered a basis for a finite-dimensional vector space. Participants explore the definitions and implications of linear independence and spanning sets in the context of vector spaces.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Mathematical reasoning

Main Points Raised

  • Some participants assert that to prove a set of vectors is a basis for a finite-dimensional vector space, it is sufficient to show that the set is linearly independent.
  • Others argue that it is necessary to demonstrate that the number of vectors in the set matches the dimension of the vector space, especially if the dimension is unknown.
  • A participant highlights that a basis must consist of linearly independent vectors that span the entire space, referencing a theorem about the relationship between different bases of the same space.
  • Another participant mentions the replacement theorem, stating that if the dimension is known, any linearly independent subset of the same size as the dimension will form a basis.
  • One participant provides a counterexample to illustrate that a linearly independent set may not necessarily be a basis unless it spans the space.
  • Clarifications are made regarding the definitions of finite-dimensional vector spaces and the conditions under which a set of vectors can be considered a basis.

Areas of Agreement / Disagreement

Participants express differing views on whether linear independence alone is sufficient to establish a basis for a finite-dimensional vector space. Some agree that knowing the dimension allows for a simpler proof, while others maintain that additional conditions must be met regardless of dimension.

Contextual Notes

There is an ongoing discussion about the definitions and implications of linear independence and spanning sets, with some participants pointing out potential circular reasoning in the definitions provided.

Who May Find This Useful

This discussion may be useful for students and educators in linear algebra, particularly those exploring the concepts of vector spaces, bases, and the properties of linear independence.

Bachelier
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Why is it enough to prove that a set of vectors is a BASIS to a FINITE DIMENSIONAL Vector Space, it is enough to show that it is Linearly Independent.

No Need to prove that it spans the whole vector space?
 
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Hint: What is the definition of finite-dimensional? A vector space is n-dimensional, if...
 
Fredrik said:
Hint: What is the definition of finite-dimensional? A vector space is n-dimensional, if...

...if it has a basis consisting of a finite number of vectors. In this case n vectors.
This is my point, we still have to show that the number of elements in the set is equal to the dimension of the vector space V. For instance if the dim is unknown, then we must show the set spans. Otherwise using just the fact that V is finite dimensional is not enough.
Am I reading this correctly?

Thank you.
 
A basis is a set of linearly independent vectors that span all the space. The first important theorem tells us that if one basis is finite then any other basis is also finite and they have the same number of vectors. This common number is then called the dimension of the space.
 
a basis is any set of linearly independent vectors that span a space V.
If you are given a dimension for a vector space V, then by the replacement theorem , any linearly independent subset of V that's of size n will form a basis for V
 
Bachelier said:
...if it has a basis consisting of a finite number of vectors. In this case n vectors.
OK, with that definition things get circular. The one I had in mind is that dim V=n if there exists a linearly independent subset of V with n members but no linearly independent subset of V with n+1 members. Suppose that dim V=n, and that B is a linearly independent subset of V with n members. Let x be an arbitrary member of V. If x is in B, then x is obviously a linear combination of the members of B. If x is in V-B, then [itex]B\cup\{x\}[/itex] is linearly dependent (since it has n+1 members), so x is a linear combination of the members of B in this case too.
 
Last edited:
Perhaps I am reading the opening post different than you guys, but my answer: it is NOT enough, since otherwise any linearly independent set - whether or not it is maximal - would be a basis.

The set

[tex]\{(1,0,0),(0,1,0)\}\subset\mathbb{R}^3[/tex]

is linearly independent, but not a basis.

The set

[tex]\{(1,0,0),(0,1,0),(0,0,1)\}\subset\mathbb{R}^3[/tex]

is also linearly independent, but moreover it spans R^3, hence it is a basis.

Of course, if you know the dimension of the vector space, say n, then in order to prove that some set consisting of precisely n vectors is a basis, it IS enough only to show linear independence. But that was not included in the question.
 
The OP should have said "a set of n vectors" and "an n-dimensional vector space" instead of "a set of vectors" and "a finite dimensional vector space". I sort of assumed that that's what he meant, and then quickly forgot that he actually said something else.
 
I thought the question was pretty straight-forward by itself and needs no clarification.. And yes, I agree with Landau and his counterexample. It simply isn't enough.
 
  • #10
Great answers everbody. Thank you very much.
 

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