Linear Algebra (Linearly Independent vs. Linearly Dependent)

In summary, the statement "If S = {v1, v2, v3} where v1, v2 and v3 are in \mathbb{R}^2, then the vectors v1, v2 and v3 are linearly independent" is true.
  • #1
DanielFaraday
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Homework Statement



If S = {v1, v2, v3} where v1, v2 and v3 are in [itex]\mathbb{R}^2[/itex], then the vectors v1, v2 and v3 are linearly independent.

Homework Equations


None

The Attempt at a Solution


I thought the answer was true, but I know the correct answer is false and I'm not sure why. Here was my reasoning for true:

If this implies that these three vectors span [itex]\mathbb{R}^3[/itex], then they must be linearly independent. If they weren't, then they would only span [itex]\mathbb{R}^2[/itex] or [itex]\mathbb{R}^3[/itex] space.

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  • #2
So is the problem asking you whether or not this statement is true? Is there any other information given regarding what S is?
 
  • #3
Sorry. Yes, this is a true/false question. S is a set of vectors [tex]v_1, v_2 \text{ and } v_3 \text{ in }\mathbb{R}^3 \text{ space}[/tex]. That's all that is given.
 
  • #4
Okay. Cool. So if you think it is false, then you need to try and come up with a counterexample. That is, you need to find three vectors in R3 such that the three vectors are not linearly independent, i.e. they are linearly dependent.

I think what you have as a solution to it being true is wrong because it isn't given that S spans R3. If it was given, then what you have would be correct, but that isn't given information.
 
  • #5
Oh, I see. So the keyword is span, I suppose. I guess you can still imagine a 3-D space with these vectors even if the vectors don't span that space. OK, that makes sense.

Thanks! I posted two other T/F questions - do you think you could take a look?
 
  • #6
Can you find three distinct vectors in R^3 that are linearly dependent?
 
  • #7
VeeEight said:
Can you find three distinct vectors in R^3 that are linearly dependent?

The first picture that comes to my mind is a vector centered at the origin and two identical vectors, the first multiplied by -C and the second multiplied by C. However, this would create three vectors parallel to each other, so they would only span R^2.

What is a better way to think about it?
 
  • #8
One of the things you should have learned already is that, in a vector space of dimension n, there cannot be a set of fewer than n vectors that spans the space nor can there be a set of more than n vectors that are independent.
 
  • #9
HallsofIvy said:
One of the things you should have learned already is that, in a vector space of dimension n, there cannot be a set of fewer than n vectors that spans the space nor can there be a set of more than n vectors that are independent.

Thanks for the comment, but as I mentioned in my second post, I made a mistake in my original post. The vectors v1, v2 and v3 are in R^3, not R^2.
 
  • #10
DanielFaraday said:
The first picture that comes to my mind is a vector centered at the origin and two identical vectors, the first multiplied by -C and the second multiplied by C. However, this would create three vectors parallel to each other, so they would only span R^2.

What is a better way to think about it?

Well if you have three vectors that are just multiples of each other (i.e. they are linearly dependent), then no two out of the three are linearly independent, which means that they couldn't span [itex]\mathbb{R}^2[/itex]. They would actually only span [itex]\mathbb{R}[/itex]. The example you gave is definitely a counterexample to your original problem though. Good job.
 
  • #11
n!kofeyn said:
Well if you have three vectors that are just multiples of each other (i.e. they are linearly dependent), then no two out of the three are linearly independent, which means that they couldn't span [itex]\mathbb{R}^2[/itex]. They would actually only span [itex]\mathbb{R}[/itex]. The example you gave is definitely a counterexample to your original problem though. Good job.

I see. Thanks!
 

1. What is the difference between linearly independent and linearly dependent vectors?

Linearly independent vectors are a set of vectors that cannot be written as a linear combination of each other. This means that none of the vectors in the set can be expressed as a multiple of another vector in the set. On the other hand, linearly dependent vectors are a set of vectors that can be written as a linear combination of each other. This means that at least one of the vectors in the set can be expressed as a multiple of another vector in the set.

2. How can you tell if a set of vectors is linearly independent or linearly dependent?

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. In other words, the only way to get a linear combination of the vectors to equal the zero vector is by setting all the coefficients to zero. If there exists a non-trivial solution (where at least one of the coefficients is not zero), then the vectors are linearly dependent.

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

No, a set of two vectors cannot be both linearly independent and linearly dependent. This is because a set of two vectors can only be linearly dependent if one vector is a multiple of the other, which means they are not linearly independent. Similarly, if a set of two vectors is linearly independent, it means that neither vector can be expressed as a multiple of the other, making them linearly dependent.

4. How does linear independence/dependence affect the solutions to a system of linear equations?

If the vectors in a system of linear equations are linearly independent, then there is a unique solution to the system. This means that the system has a single point of intersection (if the equations are graphed in two dimensions) or a single point of intersection with each plane (if the equations are graphed in three dimensions). On the other hand, if the vectors are linearly dependent, there are either infinitely many solutions (if the system is consistent) or no solutions (if the system is inconsistent).

5. Can a set of vectors be linearly independent in one dimension but linearly dependent in another dimension?

Yes, a set of vectors can be linearly independent in one dimension but linearly dependent in another dimension. This means that the vectors are linearly independent when considered individually, but when combined with other vectors, they become linearly dependent. For example, the vectors (1,0) and (0,1) are linearly independent in two dimensions, but when combined with the vector (1,1), they become linearly dependent in three dimensions.

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