Find a basis for vector space

If you want to be fancy you could say that the "basis" is a(1, 1, 1) with the scalar a being any real number.In summary, the set of solutions to the system of linear equations a - 2b + c = 0 and 2a - 3b + c = 0 is a subspace of R^3 defined by a = b = c. To find a basis for this subspace, one possible choice is (1, 1, 1) as it satisfies both equations and can be written as a linear combination of itself. This basis vector must have three components as
  • #1
vsage
Ok another question:

13. The set of solutions to the system of linear equations

a - 2b + c = 0
2a - 3b + c = 0

is a subspace of R^3. Find a basis for this subspace

The book claims one of the possible bases is (1, 1, 1) but I don't see how. I mean I realize a = b = c from the above just am not making the connection why there has to be THREE 1's. Originally I had (1, 1) but I really can't remember why. Is it because since a, b and c are equal, all the solutions to the above in (a, b, c) format are given by d(1, 1, 1) where d is a scalar?
 
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  • #2
vsage said:
Ok another question:

13. The set of solutions to the system of linear equations

a - 2b + c = 0
2a - 3b + c = 0

is a subspace of R^3. Find a basis for this subspace

Makes perfect sense. Think about it...the set of solutions is a set of real numbers (a, b, c) that satisfy both linear equations. It sounds like such a set has three components, necessitating that it be a vector in R3. In fact, a = b = c is satistied by vectors of the form (1, 1, 1)...(2, 2, 2), ...(3, 3, 3). But all of these can be written as linear combinations of (1, 1, 1). Which is exactly what you said...all others are scalar multiples of that vector. The subspace is the line through the origin. One vector is sufficient to span a 1-dimensional subspace, but that subspace is located in R3, so the basis vector must have three components.

Another way to look at it...those two equations define two planes in R3, (where in this case our coordinate space is formed from the mutually orthogonal a, b, and c axes) and evidently they intersect in the line a = b = c.
 
Last edited:
  • #3
If you were just trying to SOLVE the equations, you would subract one from the other to cancel the "c" terms and get -a+ b= 0. Okay, a= b. Now put that back into the first equation: setting a= b gives -a+ c= 0 so a= c. If you put a= b= c into the second equation, you find it is automatically solved: any numbers a= b= c satisfy both equations so (a, b, c)= (a, a, a)= a(1, 1, 1). The have to be THREE numbers in the "basis" because your solution consists of 3 numbers, a, b, c.

(By the way, your book says "one of the possible bases" because, of course, (2, 2, 2) or (3, 3, 3) or any set of 3 identical numbers would work.
 

1. What is a basis for a vector space?

A basis for a vector space is a set of linearly independent vectors that can be used to express any vector in the vector space through linear combinations. In other words, a basis is a set of vectors that can be used as building blocks to create any vector in the space.

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

To find a basis for a vector space, you can use the span and linear independence properties. First, choose a set of vectors that span the vector space. Then, check if these vectors are linearly independent. If they are, then they form a basis for the vector space. If not, you can remove any linearly dependent vectors and repeat the process until you have a set of linearly independent vectors that span the space.

3. Can a vector space have multiple bases?

Yes, a vector space can have multiple bases. This is because there can be more than one set of linearly independent vectors that can span the vector space. However, all bases for the same vector space will have the same number of vectors, which is known as the dimension of the vector space.

4. How do you know when a set of vectors forms a basis?

A set of vectors forms a basis for a vector space if they are linearly independent and span the vector space. This means that the vectors cannot be written as scalar multiples of each other and they can be used to express any vector in the space through linear combinations.

5. Is it possible for a vector space to not have a basis?

No, every vector space must have a basis. This is because the span and linear independence properties guarantee that there will always be a set of vectors that can be used to create any vector in the space.

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