Understanding Span and Linear Independence in Vector Spaces

In summary, the conversation discusses the relationship between linearly independent subsets and spanning subsets in a vector space. The speaker argues that the two statements mentioned by the professor are not always true, giving examples to support their argument. They suggest that the concept of maximal linearly independent sets and minimal spanning sets can help explain this relationship, as they both have the same number of vectors and determine the "dimension" of the space.
  • #1
darkchild
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My professor says that a linearly independent subset of a vector space automatically spans the vector space, and that a subset of a vector space that spans the vector space is automatically linearly independent.

I don't understand why either of these is true.
 
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  • #2
they aren't. For example, a set containing a single non-zero vector is always independent but only spans in the case of a one-dimensional vector space. The set consisting of the entire vector space, on the other hand, spans the vector space but cannot be independent. You may have misunderstood your professor. A maximal linearly independent set (there is no linearly independent set containing more vectors) spans the space and a minimal spanning set (there is no smaller spanning set) is linearly independent. One can then show that all set that both span the space and are linearly independent contain the same number of vectors (the "dimension" of the space).
 

What is span?

Span refers to the set of all possible linear combinations of a given set of vectors. In other words, it is the collection of all vectors that can be created by multiplying each vector in the set by a scalar and adding them together.

What does it mean for vectors to be linearly independent?

Linear independence means that none of the vectors in a set can be written as a linear combination of the other vectors in the set. In other words, each vector in the set must contribute a unique direction to the span of the set.

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

A set of vectors is linearly independent if and only if the only solution to the equation c1v1 + c2v2 + ... + cnvn = 0 is c1 = c2 = ... = cn = 0, where c1, c2, ..., cn are scalars and v1, v2, ..., vn are the vectors in the set.

What is the relationship between span and linear independence?

If a set of vectors is linearly independent, then their span is the entire space that they are in. On the other hand, if a set of vectors is linearly dependent, then their span is a subspace of the space they are in.

Can a set of vectors be both linearly independent and linearly dependent?

No, a set of vectors cannot be both linearly independent and linearly dependent. It is either one or the other. A set of vectors is linearly independent if and only if it is not linearly dependent.

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