Dimension of a subspace question

In summary, the conversation discusses finding the dimension and basis vectors of a subspace defined by three column vectors. The individual asks for clarification on the process and the responder explains how to find the dimension using row operations and how to determine the basis vectors. The resulting dimension is 2 and the two nonzero rows in the reduced matrix are the basis vectors.
  • #1
de1337ed
11
0
I'm a little confused about some of the matrix terminology.
I have the following subspace:

span{v1, v2, v3} where v1, v2, v3 are column vectors defined as:

v1 = [1 2 3]
v2 = [4 5 6]
v3 = [5 7 9]
(pretend they are column vectors)

How am I supposed to find the dimension of the span?

My Work:

I created a 3x3 matrix using the column vectors, then I performed row operations to get it into upper triangular form. After performing these row operations, I ended up with the resulting matrix:
[1 4 5
0 -3 -3
0 0 0 ]

So because the rank(A) = 2, the dimension is 2. Am I right?
Also, how would I go about finding the basis vectors. Thank you.
 
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  • #2
If you are going to do row reduction put your vectors into the matrix as rows. So yes, you'll get dimension 2. The two nonzero rows will be basis vectors.
 

Related to Dimension of a subspace question

1. What is a subspace?

A subspace is a subset of a vector space that is closed under addition and scalar multiplication. This means that if you take any two vectors in the subspace, their sum will also be in the subspace. Additionally, if you multiply any vector in the subspace by a scalar, the result will also be in the subspace.

2. How is the dimension of a subspace determined?

The dimension of a subspace is determined by the number of linearly independent vectors in the subspace. This means that the minimum number of vectors needed to span the subspace is the same as the dimension of the subspace. For example, a subspace with two linearly independent vectors has a dimension of 2.

3. Can a subspace have a dimension of 0?

Yes, a subspace can have a dimension of 0. This means that the subspace only contains the zero vector. It is still considered a subspace because it is closed under addition and scalar multiplication.

4. What is the difference between a subspace and a basis?

A basis is a set of linearly independent vectors that span a vector space. A subspace, on the other hand, is a subset of a vector space that is closed under addition and scalar multiplication. In other words, a basis is a set of vectors that can be used to represent any vector in a vector space, while a subspace is a subset of a vector space that shares some of the same properties.

5. How do you find the dimension of a subspace?

To find the dimension of a subspace, you need to find the number of linearly independent vectors in the subspace. This can be done by using Gaussian elimination or by finding the null space of the subspace's matrix representation. Once you have the linearly independent vectors, the number of vectors is the same as the dimension of the subspace.

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