Finding a basis for vector spaces

In summary, when finding a basis for algebraically defined vector spaces with multiple conditions, it is important to algebraically eliminate variables to find a set of basis vectors. In the first example, eliminating a results in the basis {(-2,1,0),(-3,0,1)}, while in the second example, eliminating two variables results in the basis {(k1,k2,k3)}.
  • #1
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I'm having trouble finding a basis for algebraically defined vector spaces where there is more than one condition. For instance, I can easily find a basis for the vector space in R^3 defined by a+2b+3c=0 (where a,b,c are the elements of the vector), but I have no idea what to do when the vector space is defined by something like a-b-c=0 & 2a+3b+8c=0.

For the first example I would write that every vector in the space has to be of the form (-2b-3c, b, c) = b(-2,1,0) + c(-3,0,1), so a basis for the vector space would be {(-2,1,0),(-3,0,1)}. I have no idea what to do for the second example.
 
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  • #2
You got to (-2b-3c, b, c) by just algebraically eliminating a. Now b and c are free variables. For the second case do the same thing, but eliminate two variables. So the result is, say, (k1*c,k2*c,k3*c). Then the basis is {(k1,k2,k3)}.
 
  • #3
Dang! I wrote out a brilliant explanation, then went back and read Dick's. His was better!
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of vectors and operations that can be performed on those vectors. These operations include addition and scalar multiplication, and the set of vectors must follow certain rules and properties in order to be considered a vector space.

2. Why is it important to find a basis for a vector space?

Finding a basis for a vector space allows us to represent any vector in that space as a linear combination of the basis vectors. This helps us to understand the structure of the vector space and make calculations and proofs easier to handle.

3. How do you find a basis for a vector space?

To find a basis for a vector space, we need to find a set of linearly independent vectors that span the entire space. This can be done by first finding a set of vectors that span the space, and then using the Gram-Schmidt process to make them linearly independent.

4. Can a vector space have more than one basis?

Yes, a vector space can have multiple bases. In fact, any set of linearly independent vectors that span the space can be considered a basis. However, all bases for a given vector space will have the same number of vectors, which is known as the dimension of the space.

5. How do you determine the dimension of a vector space?

The dimension of a vector space is equal to the number of vectors in any basis for that space. It can also be determined by counting the number of variables in the vector equations that describe the space, or by using the rank-nullity theorem.

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