What is the basis and dimension of a subspace given by (1,-2,3,-1), (1,1,-2,3)?

In summary, to determine the basis and dimension of a subspace given by a set of vectors, we can check for linear dependence and use those vectors as a basis if they are linearly independent. If the vectors are dependent, we can choose one of them as a basis, resulting in a dimension of 1. We can also determine the dimension of the subspace by counting the number of vectors in the spanning set. Additionally, putting the basis vectors in a matrix and using row-echelon form does not change their linear independence and they can still be used as a basis for the subspace.
  • #1
Fanta
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say we are given a subspace like this:

Being W the subspace of R generated by (1,-2,3,-1), (1,1,-2,3) determine a basis and the dimension of the subspace.

Won't the vectors given work as a basis, as long as they are linearly independent?
If so, all we have to do is check for dependance, and if the system is dependent, we would choose one of the vectors as a base, and the dimention would be 1. if it was independent, the basis would be both of those vectors, and the dimention would be 2.

By the same logic, If I was asked to determine the dimention of the subspace generated by those vectors, i'd just check for linear dependance.
Is this right?

By the way, should I simplify the basis by putting them in a matrix and getting it to row-echelon form? would the basis still "work" after that?
 
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  • #2
The two vectors are obviously linearly independent; if they were dependent, one would be a constant multiple of the other. If you had been given three vectors, you wouldn't be able to tell by inspection that the three vectors were linearly independent.

Since the two vectors give generate the subspace in question, they span the subspace, and hence form a basis for it.

The dimension of a vector subspace is equal to the number of vectors in the spanning set for the subspace.
 

FAQ: What is the basis and dimension of a subspace given by (1,-2,3,-1), (1,1,-2,3)?

What is a subspace?

A subspace is a subset of a vector space that satisfies the same properties as the original vector space. This means that it contains the zero vector, is closed under vector addition and scalar multiplication, and is non-empty.

Why is finding a basis for a subspace important?

A basis for a subspace is important because it allows us to represent all vectors in the subspace using a linear combination of basis vectors. This makes it easier to perform calculations and determine properties of the subspace.

How do you find a basis for a subspace?

To find a basis for a subspace, you can use the following steps:
1. Determine the dimension of the subspace.
2. Choose a set of linearly independent vectors in the subspace.
3. If the number of vectors chosen is equal to the dimension of the subspace, then these vectors form a basis.
4. If the number of vectors chosen is less than the dimension of the subspace, then use the Gram-Schmidt process to find additional linearly independent vectors until the desired dimension is reached.

Can a subspace have multiple bases?

Yes, a subspace can have multiple bases. This is because there are usually many different sets of linearly independent vectors that can span the same subspace.

Is the zero vector always part of a basis for a subspace?

Yes, the zero vector is always part of a basis for a subspace. This is because the zero vector is always in the subspace and is a necessary component for any linear combination of basis vectors to produce all vectors in the subspace.

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