Can explain to me what is mean of span?

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Discussion Overview

The discussion centers around the concept of "span" in vector spaces, particularly in relation to linear combinations of vectors. Participants explore the definitions, implications, and examples of span in various dimensions, including R^2 and R^3, while also touching on related concepts such as linear independence and dependence.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants seek clarification on the definition of span, noting that it refers to the ability to express any vector in a space as a linear combination of a given set of vectors.
  • One participant provides an example of a set of vectors in R^2 that spans the space, illustrating how any vector can be represented as a linear combination of the basis vectors.
  • Another participant questions the relationship between span and linear independence, suggesting that a linearly independent set of vectors must span the space they occupy.
  • Some participants discuss conditions under which a set of vectors does not span a space, using examples to illustrate vectors that cannot be expressed as linear combinations of others.
  • One participant draws an analogy between the mathematical concept of span and its English meaning, suggesting that span indicates the ability to "go across" a space using the vectors.
  • Another participant emphasizes the dimensionality aspect, explaining how a single vector spans a line, while two independent vectors can span a plane in higher dimensions.

Areas of Agreement / Disagreement

Participants generally agree on the basic definition of span and its relation to linear combinations, but there are differing views on the implications of linear independence and the conditions under which a set of vectors spans a space. The discussion remains unresolved regarding specific scenarios where a set may not span a space.

Contextual Notes

Some participants express uncertainty about the concept of span and its nuances, indicating that further clarification may be needed on the relationship between span and linear independence, as well as the conditions that affect spanning.

nothGing
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can explain to me what is mean of span?
from book, it say "every vector in the space can be expressed as linear combination of the vectors, then it called the span of vector."
but i still can't catch its meaning and concept.
 
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Okay, do you know what linear combination means? The two things you can do with vectors are add them and multiply them by numbers. For example, if my set of vectors is {<1, 0, 1> , <1, 1, 0>} then all linear combinations of them are things like a<1, 0, 1>+ b<1, 1, 0>= <a, 0, a>+ <b, b, 0>= <a+b, b, a>. Things like that are in the "span" of {<1, 0, 1>, <1, 1, 0>}. As long as I stay in that span, I can just focus on <1, 0, 1> and <1, 1, 0> and all other vectors (in that span) are taken care of! I can, by the way, immediately see that <3, 2, 1> is in that span and that <3, 2, 2> is not (look at whether the first component is the sum of the other two).

There are an infinite number of vectors in any vector space and we would like to be able to write all of them in terms of some smaller set. If we can then we say that set "spans" the entire vector space.
 


the smaller set in R^2 is {<1,0> , <0,1>}, this set "spans" entire R^2, correct?

how can span related to linear independence of the set of vectors, S in a vector space, V ?
if the set of vectors, S is "linearly independent or linearly dependent", then S "must" be a span of V.
or should say S spans V. correct?

under what situation or condition, S is not a span, ie the set of vectors S can't express as a linear combination of vectors in S?
because seen like all set of vectors in S can express as linear combination of vectors in S.
 


Saying that a set spans a vector space means that any vector in the vector space can be written as a linear combination of vectors in the set- possibly in more than one way. For example, the set {<1, 0>, <0, 1>, <1, 1>} spans R2 because any vector can be written <a, b> = a<1, 0>+ b<0, 1>. In fact, <a, b>= (a-x)<1, 0>+ (b-x)<0, 1>- x<1, 1,> for any number x.

If a set of vectors is independent, it may not be that all vectors can be written as a linear combination of vectors in the set, but those that can be can be written in only one way.

It is not too hard to show that if a set of vectors spans the space then no larger set can be independent and that if a set of vectors is independent, then no smaller set can span the set. There always exist a specific number of vectors that can both be independent ans span the space.

If a set of vector both spans the space and is independent, then every vector in the vector space can be written as a linear combination of vectors in the set in exactly one way. That is very nice!
 


"span" is still obscure to me.
but in overall, I am more nearer to it.
your explanation really useful.
thank you. ^^
 


The "span" of a set of vectors in a space is somewhat related to the meaning of this word in English. In a non-mathematics context, we can talk about a bridge that spans (or goes across) a river. In the mathematical context, you might say we can say that a certain set of vectors "goes across" a space, in the sense that I can use the vectors in the set to get to a specific vector. How I use the vectors is to form a linear combination of them, which is the sum of scalar multiples of the vectors.

For example, consider this set of vectors in R3: {(1, 0, 0), (0, 1, 0)}. Do the vectors in this set span R3? There are lots of vectors in R3 that can be written as a linear combination of these vectors. One that can be written this way is (2, 1, 0) = 2(1, 0, 1) + 1(0, 1, 0). On the other hand there are also lots of vectors in R3 that are not linear combinations of the two vectors - there is no linear combination of (1, 0, 0) and (0, 1, 0) that produces (2, 1, 5). For this reason, the vectors (1, 0, 0) and (0, 1, 0) do not span R3.

Although the vectors of my example, (1, 0, 0) and (0, 1, 0), do not span R3, they do span a two-dimensional subspace of R3, the x-y plane.
 


I think it helps to think of span just as Mark44 explains it.
In R^3 a vector such as <1, 0, 0> would span a line, in this case the x-axis. You can find any point on the x-axis by multiplying the vector with a scalar; 3<1, 0, 0> gives you a point (3,0,0) on the x-axis.

Then if you have two independent (not pointing in the same direction) vectors such as <1, 0, 0> and <0, 1, 0> they span a plane in R^3. You can call this plane a subspace of R^3, just as Mark44 writes. If you want to find a point on that plane, you take linear combinations of the vectors. Basically you move along one vector, then move along the other and add up. a<1, 0, 0> + b<0, 1, 0>.
 

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