I Linear independence of three vectors

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For three vectors to be linearly independent, it is not sufficient to check the independence of each pair; all vectors must be considered together. If two vectors are linearly independent, the third vector must also not be expressible as a linear combination of the first two. A vector can be independent of one vector while being dependent on another, highlighting the complexity of linear independence in higher dimensions. The discussion emphasizes that linear independence requires a holistic approach rather than pairwise checks. Therefore, the initial question about the independence of vector c from b, given its independence from a, is answered negatively; independence must be verified among all vectors collectively.
Salmone
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If I've got three vectors ##\vec{a}##, ##\vec{b}## and ##\vec{c}## and ##\vec{a}##, ##\vec{b}## are linearly independent and ##\vec{c}## is linearly independent from ##\vec{a}##, is ##\vec{c}## also linearly independent from ##\vec{b}##?
 
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Salmone said:
If I've got three vectors ##\vec{a}##, ##\vec{b}## and ##\vec{c}## and ##\vec{a}##, ##\vec{b}## are linearly independent and ##\vec{c}## is linearly independent from ##\vec{a}##, is ##\vec{c}## also linearly independent from ##\vec{b}##?
You mean assuming ##\vec c \ne \vec b##?
 
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PeroK said:
You mean assuming ##\vec c \ne \vec b##?
Yes.
 
Salmone said:
Yes.
Under what circumstances are two vectors linearly independent? There's a fairly simple criterion.
 
PeroK said:
Under what circumstances are two vectors linearly independent? There's a fairly simple criterion.
If the linear combination of the two is equal to ##0## only when both coefficients are equal to ##0##.
 
Salmone said:
Yes.
Can you use the ##\vec c = \vec b ## counterexample to think up a whole family of other counterexamples?
 
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Salmone said:
If the linear combination of the two is equal to ##0## only when both coefficients are equal to ##0##.
Okay, but for only two vectors that implies something simple.
 
Salmone said:
If I've got three vectors ##\vec{a}##, ##\vec{b}## and ##\vec{c}## and ##\vec{a}##, ##\vec{b}## are linearly independent and ##\vec{c}## is linearly independent from ##\vec{a}##, is ##\vec{c}## also linearly independent from ##\vec{b}##?

PeroK said:
Under what circumstances are two vectors linearly independent? There's a fairly simple criterion.

Salmone said:
If the linear combination of the two is equal to 0 only when both coefficients are equal to 0.
What does it mean geometrically if two vectors are linearly independent? I believe @PeroK is trying to get you to think in this direction.
 
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Mark44 said:
What does it mean geometrically if two vectors are linearly independent? I believe @PeroK is trying to get you to think in this direction.
They are orthogonal?
 
  • #10
Salmone said:
That they are orthogonal?
There's no such thing as "orthogonal" until you define an inner product on your vector space.

The answer is that ##\vec a## and ##\vec b## are linearly independent as long as one is not a scalar multiple of the other. The only vectors that are linearly dependent with ##\vec a## are vectors of the form ##\lambda \vec a## for some scalar ##\lambda##.
 
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  • #11
Hi,@Salmone , a set of vectors ##\{\vec{u_1},\vec{u_2},\ldots{\vec{u_{k}}}\}## is linearly independent ##\Longleftrightarrow{\lambda_{1}\vec{u_1}+\lambda_{2}\vec{u_2}+\ldots{+\lambda_{k}\vec{u_{k}}}=\vec{0}}##, then ##\lambda_1=\lambda_2=\ldots{=\lambda_{k}=0}##,...Hmm, I think I'm late, :smile:
 
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  • #12
PeroK said:
There's no such thing as "orthogonal" until you define an inner product on your vector space.

The answer is that ##\vec a## and ##\vec b## are linearly independent as long as one is not a scalar multiple of the other. The only vectors that are linearly dependent with ##\vec a## are vectors of the form ##\lambda \vec a## for some scalar ##\lambda##.
Okay, so can we say the same for more than three vectors. For example vectors ##\vec{a},\vec{b},\vec{c}## are linearly independent and a fourth vector ##\vec{d}## is linearly independent to ##\vec{a}## then it is linearly independent to ##\vec{b}## and ##\vec{c}## if ##\vec{d} \neq \vec{b} \neq \vec{c}##
 
  • #13
Salmone said:
Okay, so can we say the same for more than three vectors. For example vectors ##\vec{a},\vec{b},\vec{c}## are linearly independent and a fourth vector ##\vec{d}## is linearly independent to ##\vec{a}## then it is linearly independent to ##\vec{b}## and ##\vec{c}## if ##\vec{d} \neq \vec{b} \neq \vec{c}##
It doesn't matter how many vectors you have. Linear independence between any pair of vectors is a simple matter or not being mutiples of each other.

It's only when you get to three or more vectors that linear independence becomes non-trivial.
 
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  • #14
PeroK said:
It doesn't matter how many vectors you have. Linear independence between any pair of vectors is a simple matter or not being mutiples of each other.

It's only when you get to three or more vectors that linear independence becomes non-trivial.
So it's yes? If a vector is linearly independent on another vector and this last one is LI to another vector and so on, they are all LI?
 
  • #15
Salmone said:
So it's yes? If a vector is linearly independent on another vector and this last one is LI to another vector and so on, they are all LI?
Definitely not.
 
  • #16
PeroK said:
Definitely not.
So I can't understand your previous answer "It doesn't matter how many vectors you have."
 
  • #17
mcastillo356 said:
Hi,@Salmone , a set of vectors ##\{\vec{u_1},\vec{u_2},\ldots{\vec{u_{k}}}\}## is linearly independent ##\Longleftrightarrow{\lambda_{1}\vec{u_1}+\lambda_{2}\vec{u_2}+\ldots{+\lambda_{k}\vec{u_{k}}}=\vec{0}}##, then ##\lambda_1=\lambda_2=\ldots{=\lambda_{k}=0}##,...Hmm, I think I'm late, :smile:
That's not quite right. That set of vectors is linearly independent iff the only solution to the equation ##c_1x_1 + c_2x_2 + \dots + c_nx_n = 0## is ##c_1 = c_2 = \dots = c_n = 0##

Consider the vectors x, 2x, and 3x. I notice that for the equation ##c_1x + c_2*2x + c_3*3x = 0##, that ##c_1 = c_2 = c_3 = 0## is a solution. Can you conclude that these vectors are linearly independent?
 
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  • #18
Salmone said:
So it's yes? If a vector is linearly independent on another vector and this last one is LI to another vector and so on, they are all LI?
No. Draw a picture to see why the above isn't true.

What @PeroK was saying is that it's easy to determine whether two vectors are dependent. If they are, they either point the same direction or in opposite directions. I.e., they are either parallel or antiparallel (point in opposite directions). That's what "scalar multiples" of one another means.

If you have three or more vectors it's harder to tell whether they are linearly dependent or linearly independent.
 
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  • #19
Mark44 said:
No. Draw a picture to see why the above isn't true.

What @PeroK was saying is that it's easy to determine whether two vectors are dependent. If they are, they either point the same direction or in opposite directions. I.e., they are either parallel or antiparallel (point in opposite directions). That's what "scalar multiples" of one another means.

If you have three or more vectors it's harder to tell whether they are linearly dependent or linearly independent.
Ok and so what is the answer to my first question? Now I'm way more confused.
 
  • #20
Salmone said:
Ok and so what is the answer to my first question? Now I'm way more confused.
We're not going to just tell you the answer, but we'll help you arrive at it. If you draw a picture of three vectors, you'll probably get the answer in short order.
 
  • #21
Mark44 said:
We're not going to just tell you the answer, but we'll help you arrive at it. If you draw a picture of three vectors, you'll probably get the answer in short order.
I drew the three vectors and have no idea what I am supposed to figure out from this.
 
  • #22
You have said that if ##\vec c = \vec b##, then it is not true. In fact, if ##\vec c## is a multiple of ##\vec b##, then it is not true (if this is not clear to you, then you should prove it). In fact, what can you say if ##\vec c## has even a tiny component that is a multiple of ##\vec b##? So what should the answer to the problem be?
 
  • #23
FactChecker said:
You have said that if ##\vec c = \vec b##, then it is not true. In fact, if ##\vec c## is a multiple of ##\vec b##, then it is not true (if this is not clear to you, then you should prove it). In fact, what can you say if ##\vec c## has even a tiny component that is a multiple of ##\vec b##? So what should the answer to the problem be?
If ##\vec{c}## has a tiny component that is a multiple of ##\vec{b}## they are linearly indipendent.
 
  • #24
Mark44 said:
We're not going to just tell you the answer, but we'll help you arrive at it. If you draw a picture of three vectors, you'll probably get the answer in short order.
What I can imagine is that: if ##\vec{a}## and ##\vec{b}## are linearly independent then they are not a multiple of each other and if ##\vec{c}## is linearly independent with ##\vec{a}## the same can be said of these two BUT, since ##\vec{c}## and ##\vec{b}## are different they cannot even be multiples of each other so the answer should be yes, right?
 
  • #25
Due to an error on one poster's part, I have deleted that post as well as another post that pointed out the error.
 
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  • #26
Salmone said:
I drew the three vectors and have no idea what I am supposed to figure out from this.
Can you post the picture you drew?
 
  • #27
Salmone said:
What I can imagine is that: if ##\vec{a}## and ##\vec{b}## are linearly independent then they are not a multiple of each other and if ##\vec{c}## is linearly independent with ##\vec{a}## the same can be said of these two BUT, since ##\vec{c}## and ##\vec{b}## are different they cannot even be multiples of each other so the answer should be yes, right?
Your argument is similar to:
  1. 5 is not a multiple of 2
  2. 5 is not a multiple of 4
  3. 4 isn't equal to 2; therefore, 4 is not a multiple of 2.
See the problem?
 
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  • #28
Hi, PF, this is hardwork!:biggrin:(for me, of course)
##\{(0,0,1),(0,0,2),(0,0,3)\}## is dependent, though could be multyplied by ##\lambda_1=\lambda_2=\lambda_3=0## to be ##\vec{0}##
Thanks, @Mark44 !
Where I wrote "then", it is ##\iff##
Quite sure:smile:
 
  • #29
vela said:
Your argument is similar to:
  1. 5 is not a multiple of 2
  2. 5 is not a multiple of 4
  3. 4 isn't equal to 2; therefore, 4 is not a multiple of 2.
See the problem?
No, ##5*2/5=2## so they are the same vector, ##2/5## is a scalar. If ##\vec{a}## doesn't the same direction of ##\vec{b}## and ##\vec{c}## doesn't have the same direction of ##\vec{a}## and ##\vec{c} \neq \vec{b}##, how can ##\vec{c}## and ##\vec{b}## have the same direction?
 
  • #30
Mark44 said:
Can you post the picture you drew?
media_3aa_3aa3ee1f-e593-4eca-97a3-861e72759640_phpvKKeK6.png

It seems to me that three vectors like these are linearly independent
 

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