Dimension of the span of a set of vectors

In summary: If dim(span(A)) = n, then any basis for span(A) must have at least n elements, so the set of vectors A must have at least n elements.
  • #1
MostlyHarmless
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My linear algebra is a bit rusty.

Let ##A=\{\bar{v}_1, \dots, \bar{v}_1\}## be a set of vectors in ##R^n##. Can dim(span##(A))=n## without spanning ##R^n##?

I guess I'm unclear on how to interpret the dimension of the span of a set of vectors.
 
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  • #2
The span of a set of vectors is a vector space. There cannot be a proper n-dimensional subspace of an n-dimensional vector space. Any n-dimensional subspace must be the whole thing.

That is one area where vector spaces differ from modules.
 
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  • #3
MostlyHarmless said:
My linear algebra is a bit rusty.

Let ##A=\{\bar{v}_1, \dots, \bar{v}_1\}## be a set of vectors in ##R^n##. Can dim(span##(A))=n## without spanning ##R^n##?

I guess I'm unclear on how to interpret the dimension of the span of a set of vectors.
Are there n vectors in A? Your subscripts all appear to be 1. Presumably you meant ##\{\bar{v}_1, \dots, \bar{v}_n\}##.
 
  • #4
Mark44 said:
Are there n vectors in A? Your subscripts all appear to be 1. Presumably you meant ##\{\bar{v}_1, \dots, \bar{v}_n\}##.

Yeah that second, 1 should have been an m. Not necessarily an n. (at least I don't think it should necessarily be an n).
 
  • #5
andrewkirk said:
The span of a set of vectors is a vector space. There cannot be a proper n-dimensional subspace of an n-dimensional vector space. Any n-dimensional subspace must be the whole thing.

That is one area where vector spaces differ from modules.

Ok, this is exactly what I needed to know!

I've not gotten to modules yet. I'm taking a second graduate Algebra class next semester though. I'm told we will finally get into them then.
 
  • #6
MostlyHarmless said:
Yeah that second, 1 should have been an m. Not necessarily an n. (at least I don't think it should necessarily be an n).
Then you should specify some condition on m. If m < n, then your set of vectors could not possibly span ##\mathbb{R}^n##, since dim(span(A)) ##\le m < n##. If ##m \ge n##, the set of vectors might span ##\mathbb{R}^n##, or might not.
 
  • #7
The only condition I wanted on m is that it was not necessarily equal to n. So that it was truly an arbitrary set of vectors in ##R^n##. That way the question was just: "Given an arbitrary set of vectors, A, such that dim(span(A)) = n. Does A necessarily span ##R^n##?" This is a more concise way of asking the question.. I believe the two questions are equivalent though. If not, this is definitely the question I mean to ask.

Which the answer appears to be yes... as per andrewkirk.

Edit: I guess the condition that dim(span(A))=n forces the condition that ##m\geq n##.
 
  • #8
MostlyHarmless said:
Edit: I guess the condition that dim(span(A))=n forces the condition that m n .
Yes
 

1. What is the definition of the dimension of the span of a set of vectors?

The dimension of the span of a set of vectors is the minimum number of vectors needed to span the entire space in which the vectors exist. It represents the number of independent directions or degrees of freedom that the vectors can cover.

2. How do you calculate the dimension of the span of a set of vectors?

The dimension of the span of a set of vectors can be calculated by finding the rank of the matrix formed by the vectors, or by counting the linearly independent vectors in the set.

3. Can the dimension of the span of a set of vectors be greater than the number of vectors in the set?

Yes, the dimension of the span of a set of vectors can be greater than the number of vectors in the set. This is because some vectors may be linearly dependent on others, and therefore do not add to the dimension of the span.

4. How does the dimension of the span of a set of vectors relate to the concept of linear independence?

The dimension of the span of a set of vectors is directly related to the concept of linear independence. The number of linearly independent vectors in a set is equal to the dimension of the span of that set.

5. Why is the dimension of the span of a set of vectors important in linear algebra?

The dimension of the span of a set of vectors is important in linear algebra because it helps to determine the size and structure of vector spaces. It also plays a crucial role in solving systems of linear equations and understanding the behavior of linear transformations.

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