Linearly Independent Sets and Bases

This will help you see which vectors you can remove from the set and still have the space spanned.In summary, to find a basis for the space spanned by the given vectors, you need to check if any of the vectors are linear combinations of the others and remove them. The dimension of the vector space is then the maximum number of linearly independent vectors, and these vectors are said to 'span' the space. To determine which vectors can be removed, you can start by writing a general equation and solving for each vector in terms of the others.
  • #1
Hashmeer
16
0

Homework Statement


So I'm trying to find a basis for the space that is spanned by the given vectors.

{(1,0,0,1) (-2,1,-1,1) (6,-1,2,-1) (5,-3,3,-4) (0,3,-1,1)} These are written as column vectors.


Homework Equations


None really (that I know of)


The Attempt at a Solution


So I think I need to check to see if any of these vectors are linear combinations of the others and then remove those vectors. I'm kinda confused by the whole Basis idea maybe if someone can explain that it will help me understand where I need to be headed with this problem.
 
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  • #2
You need to start by thinking about [tex] \alpha_1\vec{V_1}+\alpha_2\vec{V_2}+...+\alpha_n\vec{V_n}=0 [/tex], where the V's are your n vectors, and alphas are just some coefficients.

Now if this equation has a solution (other than the trivial one of all the [tex] \alpha[/tex]'s being zero) then it means that is possible to write one or more of your vectors in terms of the others in the set (Think about this. You can just rearrange the equation and solve for a particular vector in terms of some of ther others...)

This means your vectors are not linearly independent. You keep doing this reducing your set of vectors until you get to the smallest set of vectors for which the solution to the above equation can only be the trivial alphas are zero one. The dimension of a vector space is then the maximum number of these LI vectors, and they are said to 'span' the vector space.

So you can start out by writing [tex] \alpha_1 (1,0,0,1)+\alpha_2 (-2,1,-1,1)+...=0 [/tex]
 

1. What is a linearly independent set?

A linearly independent set is a collection of vectors in a vector space where no vector can be written as a linear combination of the others. This means that none of the vectors in the set can be formed by multiplying another vector by a scalar and adding it to the other vectors in the set.

2. How do you determine if a set of vectors is linearly independent?

To determine if a set of vectors is linearly independent, you can use the determinant method. This involves setting up a matrix with the vectors as its columns and calculating the determinant. If the determinant is non-zero, then the set is linearly independent. If the determinant is zero, then the set is linearly dependent.

3. What is a basis?

A basis is a linearly independent set of vectors that span the entire vector space. This means that any vector in the vector space can be written as a linear combination of the basis vectors. A basis is useful because it allows us to represent any vector in the vector space using a unique set of coefficients.

4. Can a set of vectors be linearly independent and span the vector space at the same time?

No, a set of vectors cannot be both linearly independent and span the vector space at the same time. This is because a linearly independent set contains only vectors that are not multiples of each other, while a set that spans the vector space contains all possible linear combinations of those vectors.

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

To find a basis for a vector space, you can use the Gaussian elimination method. This involves taking the vectors in the vector space and reducing them to their reduced row echelon form. The vectors that correspond to the non-zero rows in the reduced form will form a basis for the vector space.

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