Linear Algebra - Number of vectors in a basis

In summary, the conversation discusses the concept of vector spaces and their bases. It is stated that if a vector space has a basis with 'n' vectors, then every basis in the vector space will also have 'n' vectors. Furthermore, it is mentioned that the dimension of the span of a set of vectors is the maximal number of linearly independent vectors in the set. The solution to a problem involving finding a basis for a subspace is given, and it is explained that the correct approach is to set up a matrix with each vector of the set as a column, and reduce it to row-echelon form. The resulting leading 1's in the rows correspond to the basis vectors for the subspace. It is also noted
  • #1
jinksys
123
0
As I read one linear algebra book I have, I am told that "If a vector space V has a basis with 'n' vectors, then every basis in vector space V has 'n' vectors.

So every basis in R3 has 3, every basis in R4 has 4, etc.

However, I have a problem that says:

Let S = { "five vectors" } be a set of vectors in R4.
Find a subset of S that is a basis for W = span S.

The solution goes through putting the matrix into row-echelon form, and it turns out v1, and v2 of the set S are a basis for W = Span S.

I'm confused, I thought bases of R4 had four vectors? Could someone clear this up for me?
 
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  • #2
you're correct, a basis for R4 will have 4 vectors

the diminesion of span{S} is the maximal number of linearly independent vectors in S, in your case this is 2

As such, no combination of vectors in S can be used as a basis for R4.

W = span{S} is a 2 dimensional subspace of R4
 
  • #3
Here's a simpler example in a lower-dimension space, R2.

Let W = {<-10, -5>, <2, 1>, <6, 3>}

No basis for R2 can have more than two vectors. W is a subset of R2, and as it turns out, W is a one-dimensional subspace of R2. The span of W, written as span(W), is the set of all linear combinations of the vectors in W. Geometrically, span(W) is a line through the origin, and passing through the point (2, 1).

Again, span(W) is a one-dimensional subspace even though the vectors in W have two components.
 
  • #4
I understand, thanks!

So if I had the problem:

S = { (1, 0, 0, 1), (0, 1, 1, 0), (1, 1, 1, 1), (-1, 1, 1, -1) }

and I am to find a basis for the subspace W = span S of M2,2...

I set up a matrix A where each vector of S is a column of A.
Reduce to row-echelon form.

I get a leading 1 in row 1 and 2, so the basis of W is {(1,0,0,1), (0,1,1,0)}.

Is this the correct way to approach this problem?
 
  • #5
jinksys said:
I understand, thanks!

So if I had the problem:

S = { (1, 0, 0, 1), (0, 1, 1, 0), (1, 1, 1, 1), (-1, 1, 1, -1) }

and I am to find a basis for the subspace W = span S of M2,2...

I set up a matrix A where each vector of S is a column of A.
Reduce to row-echelon form.

I get a leading 1 in row 1 and 2, so the basis of W is {(1,0,0,1), (0,1,1,0)}.

Is this the correct way to approach this problem?

yep, that looks good to me,

note any vector in S can be written in terms of your 2 basis vectors

also worth noting your basis vectors are orthogonal as a result of the matrix reduction
 

Related to Linear Algebra - Number of vectors in a basis

What is a basis in linear algebra?

A basis in linear algebra is a set of vectors that can be used to represent any other vector in a vector space through linear combinations. This means that any vector in the vector space can be written as a unique combination of the basis vectors.

How many vectors are needed to form a basis?

In a finite-dimensional vector space, the number of vectors needed to form a basis is equal to the dimension of the vector space. For example, in a 2-dimensional vector space, two linearly independent vectors are needed to form a basis.

What is the role of linear independence in a basis?

Linear independence is a crucial property of a basis. It means that none of the vectors in the basis can be written as a linear combination of the other vectors. This ensures that the basis vectors are unique and can be used to represent any other vector in the vector space.

Can a vector space have more than one basis?

Yes, a vector space can have multiple bases. For example, in a 2-dimensional vector space, any two linearly independent vectors can form a basis. However, all bases for the same vector space will have the same number of vectors.

How can I determine if a set of vectors forms a basis?

To determine if a set of vectors forms a basis, you can use the Gram-Schmidt process to check for linear independence. Alternatively, you can also check if the vectors span the entire vector space, which means that any vector in the space can be written as a linear combination of the basis vectors.

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