Proving span of a Set with Scalar attached to First Element

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Discussion Overview

The discussion revolves around proving the equality of spans of two sets of vectors in $\Re^n$, specifically addressing the case where one vector in the set is multiplied by a non-zero scalar. Participants explore the implications of this scalar multiplication on the linear combinations that define the spans.

Discussion Character

  • Mathematical reasoning
  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • Some participants propose that to prove $Span\{u_1,u_2,...,u_t\}=Span\{ku_1,u_2,...,u_t\}$, it is necessary to show that any vector in one span can be expressed as a vector in the other span.
  • One participant suggests that if $v \in V$ can be expressed as a linear combination of the vectors in $S$, then it can also be rewritten to show it belongs to $W$, the span of $S_k$.
  • Another participant emphasizes the importance of the condition $k \neq 0$, noting that this allows for the scaling of vectors without losing their linear independence.
  • There is a discussion about the necessity of defining the coefficients in the linear combinations correctly, with suggestions on how to relate the coefficients from one span to the other.

Areas of Agreement / Disagreement

Participants generally agree on the approach to proving the equality of spans through linear combinations, but there are differing opinions on the best way to articulate the relationships between the coefficients involved. The discussion remains somewhat unresolved as participants refine their arguments and clarify their reasoning.

Contextual Notes

Some participants note that the proof relies on the assumption that $k$ is non-zero, which is critical for the validity of the arguments presented. There is also an acknowledgment of the need to carefully define the relationships between the coefficients in the linear combinations.

shen07
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hi Guys, i Needed your help to prove out the following, thanks in advance;

Let u1,u2,...,ut be vectors in $\Re^n$ and $k\in\Re ,k\neq0.$ Prove that

$Span\{u_1,u_2,...,u_t\}=Span\{ku_1,u_2,...,u_t\}$
 
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shen07 said:
hi Guys, i Needed your help to prove out the following, thanks in advance;

Let u1,u2,...,ut be vectors in $\Re^n$ and $k\in\Re ,k\neq0.$ Prove that

$Span\{u_1,u_2,...,u_t\}=Span\{ku_1,u_2,...,u_t\}$

i started working like this, hope you can help me further,

let $S=\{u_1,u_2,...,u_t\}\\\\\,S_k=\{ku_1,u_2,...,u_t\}$
then there exist Vector Spaces $V=L(S)\\\\\&\\\\W=L(S_k)$

Now let $v \in V,\alpha\in\Re$
$v=\alpha_1u_1+\alpha_2u_2+...+\alpha_tu_t$let $w \in W,\gamma\in\Re$
$w=\gamma_1(ku_1)+\gamma_2u_2+...+\gamma_tu_t$Now am i right by saying that since $k\in\Re,k\neq0\Rightarrow\\\alpha_1=\gamma_1k \Rightarrow\\v=w\Rightarrow\\\\L(S)=L(S_k)$
 
shen07 said:
hi Guys, i Needed your help to prove out the following, thanks in advance;

Let u1,u2,...,ut be vectors in $\Re^n$ and $k\in\Re ,k\neq0.$ Prove that

$Span\{u_1,u_2,...,u_t\}=Span\{ku_1,u_2,...,u_t\}$

shen07 said:
i started working like this, hope you can help me further,

let $S=\{u_1,u_2,...,u_t\}\\\\\,S_k=\{ku_1,u_2,...,u_t\}$
then there exist Vector Spaces $V=L(S)\\\\\&\\\\W=L(S_k)$

Now let $v \in V,\alpha\in\Re$
$v=\alpha_1u_1+\alpha_2u_2+...+\alpha_tu_t$let $w \in W,\gamma\in\Re$
$w=\gamma_1(ku_1)+\gamma_2u_2+...+\gamma_tu_t$Now am i right by saying that since $k\in\Re,k\neq0\Rightarrow\\\alpha_1=\gamma_1k \Rightarrow\\v=w\Rightarrow\\\\L(S)=L(S_k)$

Hi shen07!

To prove that V and W are the same set, you should prove that any vector in V is also in W, and any vector in W is also in V.

Any vector in V can indeed be written as
$$v=\alpha_1u_1+\alpha_2u_2+...+\alpha_tu_t$$
Now is this vector v also in W?

We can rewrite it as:
$$v=\frac {\alpha_1}{k} (ku_1)+\alpha_2u_2+...+\alpha_tu_t$$
This is a linear combination of the basis of W, so yes, this vector is in W.Note that there is no need to introduce $w$, or $\gamma_i$ at this time.
But if you do, you can't just say that you already know that $\alpha_1=\gamma_1 k$.
What you could do, is say:
Pick $\gamma_1=\frac{\alpha_1}{k}$ and $\gamma_i=\alpha_i$ for $i \in \{2,...,n\}$.
Then $v=w$.Anyway, we're not completely done yet, since we still need to prove that any vector in W is also in V.
Well, any vector in W can be written as:
$$w=\gamma_1 (ku_1)+\gamma_2u_2+...+\gamma_tu_t$$
which is the same as:
$$w=(\gamma_1 k)u_1+\gamma_2u_2+...+\gamma_tu_t$$
Since this vector is a linear combination of the basis of V, it is indeed in V.

This completes the proof.
 
ILikeSerena post highlights the most important part of this exercise:

$k \neq 0$.

This is why scalars are called "scalars"...all they do is "scale" one or more coordinates (0 is obviously a special case...it annihilates one or more dimensions!).

As you can see, we can "scale" and "un-scale" to our heart's content. Physicists often do this when they change from one scale of measurement to another, like from grams to kilograms. Map-makers also use this property of scaling to fit things on a page by distorting one axis scale slightly. There really isn't anything mysterious about this (linear independence of axes means we can scale the axes independently, and still preserve linear relationships).

Vector spaces make sense, once you can get past the abstraction of the presentation. We are bringing the ability of arithmetic (which is what fields are all about) to bear on geometry (points, lines, planes, and the like).
 

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