Linear independence of 5 dimensional vectors in R^3

In summary: Yes, this doesn't make sense! These vectors are in R^5, not R^3 so that last is probably a typo. Yes, these vectors are "independent" if and only if a(2, 0, 1, -1, 0)+ b(1, 2, 0, 3, 1)+ c(4, -4, 3, -9, -2)= (0, 0, 0, 0, 0) implies that a= b= c= 0. That is the same as (2a+ b+ 4c, 2b- 4c, a+ 3c, -a+ 3b- 9c, b- 2c)= (0, 0, 0,
  • #1
quanta13
4
0
i am asked to determine whether 3 vectors which have 5 dimensions (x,y,z,w,u) are linearly dependent or independent in R^3.
it doesn't make any sense. should i ignore w and u dimensions and take x,y,z only? because if i dont, all answers would be same, doesn't matter in r^3 or R^4 etc.

the question is this:

determine whether the given vectors (2,0,1,-1,0) , (1,2,0,3,1) and (4,-4,3,-9,-2) are linearly dependent or independent in R^3?
 
Last edited:
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  • #2
Your question isn't even a complete sentence, so I don't know what you are asking. Please rewrite it in proper English. I've copied in the Physics Forums language guidelines below:

All posts must be in English. Posts in other languages will be deleted. Pay reasonable attention to written English communication standards. This includes the use of proper grammatical structure, punctuation, capitalization, spacing, and spelling. In particular, "I" is capitalized, there's a space after (but not before) a comma, a period, and other punctuation. Multiple exclamation marks are also discouraged. SMS messaging shorthand ("text-message-speak"), such as using "u" for "you", "please" for "please", or "wanna" for "want to" is not acceptable.
 
  • #3
OK, that's better. You still should capitalize "I" and use punctuation, but it is now an intelligible question. Can you tell me what it means for three vectors to be linearly dependent?
 
  • #4
phyzguy said:
OK, that's better. You still should capitalize "I" and use punctuation, but it is now an intelligible question. Can you tell me what it means for three vectors to be linearly dependent?
I am so sorry for not capitalizing ''I''.
I wrote down the question:
''determine whether the given vectors (2,0,1,-1,0) , (1,2,0,3,1) and (4,-4,3,-9,-2) are linearly dependent or independent in R^3? ''
I think it is clear what is asking. Thanks.
 
  • #5
Yes, it is clear. My question is, do you know what it means to be linearly dependent (or linearly independent)? Can you give me the definition of linear dependence?
 
  • #6
EDIT: OP: It may be a typo, and maybe it should be ##\mathbb R^5 ## instead of ##\mathbb R^3 ##. You're right that it does not make sense otherwise.
 
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  • #7
phyzguy said:
Yes, it is clear. My question is, do you know what it means to be linearly dependent (or linearly independent)? Can you give me the definition of linear dependence?
No, I don't know the definition in English. I know that when we assume c1.V1 +c2.V2+c3.V3+...+cn.Vn=0 where c are coefficients and v are our vectors, if all c coefficients are zero, vectors are linearly independent, if not then they are dependent.
 
  • #8
quanta13 said:
No, I don't know the definition in English. I know that when we assume c1.V1 +c2.V2+c3.V3+...+cn.Vn=0 where c are coefficients and v are our vectors, if all c coefficients are zero, vectors are linearly independent, if not then they are dependent.

OK. So are there constants c1, c2, c3, not equal to 0 such that c1 V1 + c2 V2 + c3 V3 = 0?

Ah, I see the confusion on ℝ3 vs ℝ5. WWGD is right. Perhaps you should ask your teacher to clarify.
 
  • #9
phyzguy said:
Ah, I see the confusion on ℝ3 vs ℝ5. WWGD is right. Perhaps you should ask your teacher to clarify.
Or correct it. The problem makes no sense whatever as written. The three given vectors don't belong to ##\mathbb{R}^3##, so questions about whether they are linearly independent or dependent are meaningless.
 
  • #10
quanta13 said:
i am asked to determine whether 3 vectors which have 5 dimensions (x,y,z,w,u) are linearly dependent or independent in R^3.
it doesn't make any sense. should i ignore w and u dimensions and take x,y,z only? because if i dont, all answers would be same, doesn't matter in r^3 or R^4 etc.

the question is this:

determine whether the given vectors (2,0,1,-1,0) , (1,2,0,3,1) and (4,-4,3,-9,-2) are linearly dependent or independent in R^3?
Yes, this doesn't make sense! These vectors are in R^5, not R^3 so that last is probably a typo. Yes, these vectors are "independent" if and only if a(2, 0, 1, -1, 0)+ b(1, 2, 0, 3, 1)+ c(4, -4, 3, -9, -2)= (0, 0, 0, 0, 0) implies that a= b= c= 0. That is the same as (2a+ b+ 4c, 2b- 4c, a+ 3c, -a+ 3b- 9c, b- 2c)= (0, 0, 0, 0, 0) which implies 2a+ b+ 4c= 0, 2b- 4c= 0, a+ 3c= 0, -a+ 3b- 9c= 0, and b- 2c= 0. Solve those equations. a= b= c= 0 is an obvious solution. Are there others?
 

1. What is the definition of linear independence?

Linear independence refers to a set of vectors in a vector space that cannot be written as a linear combination of each other. In other words, none of the vectors can be expressed as a scalar multiple of another vector.

2. How is the linear independence of 5 dimensional vectors in R^3 determined?

The linear independence of 5 dimensional vectors in R^3 is determined by checking if the determinant of the matrix formed by the vectors is equal to 0. If the determinant is 0, the vectors are linearly dependent. If the determinant is non-zero, the vectors are linearly independent.

3. Can 5 dimensional vectors in R^3 be linearly dependent?

No, 5 dimensional vectors in R^3 cannot be linearly dependent. This is because the maximum number of linearly independent vectors in R^3 is 3. Therefore, any set of 5 dimensional vectors in R^3 will always be linearly independent.

4. What is the significance of linear independence in vector spaces?

Linear independence is important in vector spaces because it allows us to determine if a set of vectors can span the entire vector space. If a set of vectors is linearly independent, it means that they are all necessary to span the vector space and cannot be replaced by other vectors.

5. How is the concept of linear independence applied in real-world situations?

The concept of linear independence is used in various fields such as physics, engineering, and computer science. In physics, linearly independent vectors are used to represent different physical quantities. In engineering, linearly independent vectors are used to represent forces and motions in different directions. In computer science, linearly independent vectors are used in data analysis and machine learning algorithms to determine the relationships between data points.

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