Question about linear independence

In summary, the conversation discusses the definition of linear independence for a set of vectors in a vector space. It is stated that for a set of linearly independent vectors, the only solution to the equation c1x1 + c2x2 + c3x3 = 0 is c1 = c2 = c3 = 0. However, for a set of linearly dependent vectors, there may be an infinite number of solutions to this equation. It is also mentioned that a linear combination of linear combinations can result in a 0 coefficient for each vector, making the set linearly dependent. The conversation also touches on how to determine if a set of three vectors is linearly independent, with one suggestion being to use the first
  • #1
Arnoldjavs3
191
3

Homework Statement


431a99f9f0a141d7aab5949fe726817a.png


Homework Equations

The Attempt at a Solution


if there exists a set with 3 vectors, and all of them are linear independent, then by definition no linear combination of the 3 vectors can equal to 0.

I believe that's an accurate definition right? So in this case, the answer is that it will always be linear independent regardless of what the value of every vector is, because they have already stated that the set is linear independent. The second part just shows an example of linear combinations correct?
 
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  • #2
Arnoldjavs3 said:

Homework Statement


431a99f9f0a141d7aab5949fe726817a.png


Homework Equations

The Attempt at a Solution


if there exists a set with 3 vectors, and all of them are linear independent, then by definition no linear combination of the 3 vectors can equal to 0.

I believe that's an accurate definition right? So in this case, the answer is that it will always be linear independent regardless of what the value of every vector is, because they have already stated that the set is linear independent. The second part just shows an example of linear combinations correct?
No. The second set is 4 vectors in a three-dimensional space.
 
  • #3
Arnoldjavs3 said:

Homework Statement


431a99f9f0a141d7aab5949fe726817a.png


Homework Equations

The Attempt at a Solution


if there exists a set with 3 vectors, and all of them are linear independent, then by definition no linear combination of the 3 vectors can equal to 0.

I believe that's an accurate definition right? So in this case, the answer is that it will always be linear independent regardless of what the value of every vector is, because they have already stated that the set is linear independent. The second part just shows an example of linear combinations correct?

I believe I could make a case that those vectors are always linearly dependent.
 
  • #4
ehild said:
No. The second set is 4 vectors in a three-dimensional space.

##u, v, w## could be vectors in any n-dimensional space.
 
  • #5
PeroK said:
##u, v, w## could be vectors in any n-dimensional space.
But the space spanned by them is three dimensional.
 
  • #6
PeroK said:
##u, v, w## could be vectors in any n-dimensional space.

So if you could make a combination that indicates that they are dependent then it would mean that it depends on values of the vectors? I'm having a hard time putting this all into perspective without examples.

ehild said:
But the space spanned by them is three dimensional.

How do you know this? I thought they were just 3, individually independent vectors in n dimensional space?
 
  • #7
ehild said:
But the space spanned by them is three dimensional.

Okay, I see what you mean.
Arnoldjavs3 said:
So if you could make a combination that indicates that they are dependent then it would mean that it depends on values of the vectors? I'm having a hard time putting this all into perspective without examples.

Suppose you take the two vectors: ##u - v - w## and ##-2u + 2v + 2w##. Are they linearly independent?
 
  • #8
Arnoldjavs3 said:
So if you could make a combination that indicates that they are dependent then it would mean that it depends on values of the vectors? I'm having a hard time putting this all into perspective without examples.
u, v, and w are linearly independent vectors. Adding any linear combination of them makes the set of the four vectors dependent.
What is the definition that a set of vectors are independent?

Arnoldjavs3 said:
I thought they were just 3, individually independent vectors in n dimensional space?

In n dimensional space there are n linearly independent vectors.
 
  • #9
PeroK said:
Okay, I see what you mean.Suppose you take the two vectors: ##u - v - w## and ##-2u + 2v + 2w##. Are they linearly independent?
No, because they are multiples of one another
ehild said:
u, v, and w are linearly independent vectors. Adding any linear combination of them makes the set of the four vectors dependent.
What is the definition that a set of vectors are independent?
In n dimensional space there are n linearly independent vectors.

So, in hte first set they are linear independent. But because set two has all vectors adding several multiples of each member it is linear dependent(hope this makes sense)? I didn't see that the second set had four members and not three. This makes a lot more sense now
 
  • #10
Arnoldjavs3 said:
I didn't see that the second set had four members and not three.
The vectors in the second set are all linear combinations of vectors ##\vec u## , ##\vec v ##, ##\vec w##. They are
##\vec a=\vec u+2\vec v +2\vec w##
##\vec b=2\vec u+5\vec v +2\vec w##
##\vec c=-3\vec u+2\vec v -4\vec w##
##\vec d=-\vec u+5\vec v +4\vec w##

Read http://mathworld.wolfram.com/LinearlyDependentVectors.html
 
  • #11
Arnoldjavs3 said:
if there exists a set with 3 vectors, and all of them are linear independent, then by definition no linear combination of the 3 vectors can equal to 0.
I don't think you understand the definition of linear independence. Given any set of three vectors that belong to some vector space, the equation ##c_1\vec{x_1} + c_1\vec{x_1} + c_1\vec{x_1} = \vec{0}## always has a solution in terms of the constants ##c_1, c_2, c_3##. This is true whether the vectors are linearly independent or linearly dependent.

The key difference is that for a set of linearly independent vectors, the only solution is ##c_1 = c_2 = c_3 = 0##. For a set of linearly dependent vectors, there will be an infinite number of solutions, including ##c_1 = c_2 = c_3 = 0##.
 
Last edited:
  • #12
Arnoldjavs3 said:
No, because they are multiples of one another

But, your original argument was that if the vectors were linearly independent then no linear combination of them is 0, so no linear combination of linear combinations can be 0. But, as you see a linear combination of linear combinations can be 0. This is because a linear combination of linear combinations can end up having a 0 coefficient for each vector.

The simplest solution is that put forward by @ehild, as there are four vectors. But, what if you had only three vectors? Just the first three, say:

##u + 2v + 2w, 2u + 5v, -3u +2v -4w##

How could you tell whether these are linearly independent?
 

1. What is linear independence?

Linear independence refers to a set of vectors in a vector space that are not dependent on each other, meaning that none of the vectors can be expressed as a linear combination of the others.

2. How can I determine if a set of vectors is linearly independent?

A set of vectors is linearly independent 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. In other words, the only way to get a linear combination of the vectors to equal zero is if all the coefficients are zero.

3. What is the difference between linear independence and linear dependence?

Linear independence means that a set of vectors is not dependent on each other, while linear dependence means that at least one vector in the set can be expressed as a linear combination of the others. In other words, linear dependence is the opposite of linear independence.

4. Why is linear independence important in mathematics and science?

Linear independence is important because it allows us to solve systems of linear equations and perform operations on vectors. It also helps us understand the structure of vector spaces and how they can be manipulated.

5. 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.

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