Linear Algebra - Dimension, Basis

In summary, the lecturer said that if the elements of W are linear combinations of the elements in V and there are more elements in W than V, then W is linearly dependent. However, if the elements of W are linear combinations of the elements in V and there are the same number of elements in W and V, then W is linearly independent.
  • #1
discoverer02
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Linear Algebra -- Dimension, Basis

Had a horrible lecture this morning and the following was presented at a lightning quick pace. I'm not sure whether I messed up my notes in my haste to get them all down or if I'm completely not understanding something.

I have two sets of vectors: W = {w1,w2,w3,...,wm} and V = {v1,v2,...,vn} V is linearly independent.
If the elements of W are linear combinations of the elements in V and there are more elements in W than V, m>n, W is linearly dependent or independent?

I wrote down W is linearly independent, but I'm thinking this is wrong.

Clarification would be VERY GREATLY APPRECIATED.

Thanks.
 
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  • #2
Linearly independent means that the vectors do not depend on each other.

Let's say that the first n vectors in W are constant multiples of the first n vectors in V, i.e.

[tex]w_n = a_n v_n[/tex]

Soyou'll agree that W will be linearly independent if it comprised only the n vectors, as V is. In fact, you'll probably agree that W is almost identical to V except in scaling.

Except now we have extra vectors in W, which are linear combinations of the vectors in V. We've run out of independent vectors in V, so we have to start adding two or more V vectors together to get a vector in W, i.e.

[tex]w_m = b^nv_n[/tex]
for m>n

So the question is, are the extra vectors in W independent of the first n vectors in W? Clearly, they cannot be, since all of the linearly independent vectors have already been used!

Therefore, W is not linearly independent.

cookiemonster
 
  • #3
Since V is linearly independent, its "span" (the set of a linear combinations of vectors in V) is a subspace- a vector space in its own right- which has dimension n. A set of vectors, such as W, in that space with more than n members CANNOT be independent. W is dependent.
 
  • #4
Thanks very much for the help. I can now try to make sense of the rest of my notes and hopefully sleep soundly tonight.
 

1. What is the definition of dimension in linear algebra?

The dimension of a vector space is the minimum number of linearly independent vectors needed to span the entire space. In other words, it is the number of vectors in a basis for the space.

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

To determine the dimension of a vector space, you can find a basis for the space and count the number of vectors in the basis. Alternatively, you can use the rank-nullity theorem to calculate the dimension as the difference between the dimension of the domain and the dimension of the null space of a linear transformation on the vector space.

3. What is a basis in linear algebra?

A basis is a set of linearly independent vectors that span a vector space. Any vector in the space can be written as a linear combination of the basis vectors, and no vector in the basis can be written as a linear combination of the other basis vectors.

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

To find a basis for a vector space, you can use the row reduction method to reduce a matrix representing the space to echelon form. The columns corresponding to the leading entries in the matrix will form a basis for the space. Alternatively, you can use the augmented matrix method to find the basis vectors directly.

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

Yes, a vector space can have infinitely many bases. For example, in two-dimensional space, any two linearly independent vectors can form a basis. Additionally, any scalar multiple of these vectors will also form a basis. However, all bases for a given vector space will have the same number of vectors, which is the dimension of the space.

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