Basis for Subspace: Find & Check LI

In summary, the conversation is about finding a basis for a subspace and determining if it is linearly independent. The definition of linear independence is discussed and applied to show that the given basis is indeed linearly independent. The conversation then moves on to discussing the direction of change of coordinates and setting up equations to determine the coordinates according to a specific basis.
  • #1
negation
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Homework Statement



Find the basis for the subspace 4x+y-3z


The Attempt at a Solution



I found that the basis is {[1;-4;0],[0;3;1]}. How do I know if it is linearly independent? I know that the mathematical definition of what LI is but how can it be applied to show in this case?
 
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  • #2
negation said:

Homework Statement



Find the basis for the subspace 4x+y-3z
That is not a subspace- it is a linear expression! I suspect that you mean "Find a basis for the subspace of R3 of all (x, y, z) satisfying 4x+ y- 3z= 0".
(If you had written "Find a basis for the subspace 4x+ y- 3z= 0" I would have had no problem, interpreting it a short hand for the above. But the "= 0" is important. Also note "a basis" not "the basis". Any vector space or subspace has an infinite number of bases.)

The Attempt at a Solution



I found that the basis is {[1;-4;0],[0;3;1]}. How do I know if it is linearly independent? I know that the mathematical definition of what LI is but how can it be applied to show in this case?
The definition of "u, v are Linearly Independent" is that "if au+ bv= 0 then a= b= 0". Applied here, that would be a[1; -4; 0]+ b[0; 3; 1]= [a; -4a+ 3b; b]= [0; 0; 0] which tells you that a= 0; -4a+ 3b= 0; b= 0. The first and third equations tell you everything you need to know, don't they?
 
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  • #3
HallsofIvy said:
That is not a subspace- it is a linear expression! I suspect that you mean "Find a basis for the subspace of R3 of all (x, y, z) satisfying 4x+ y- 3z= 0".
(If you had written "Find a basis for the subspace 4x+ y- 3z= 0" I would have had no problem, interpreting it a short hand for the above. But the "= 0" is important. Also note "a basis" not "the basis". Any vector space or subspace has an infinite number of bases.)



The definition of "u, v are Linearly Independent" is that "if au+ bv= 0 then a= b= 0". Applied here, that would be a[1; -4; 0]+ b[0; 3; 1]= [a; -4a+ 3b; b]= [0; 0; 0] which tells you that a= 0; -4a+ 3b= 0; b= 0. The first and third equations tell you everything you need to know, don't they?

How do I know a[1;-4;0]+b[0;3;1] =[0;0;0]? Does it entails from the initial premise that
4x + y - 3z = 0?

secondly, we now know the basis B to be {[1;-4;0],[0;3;1]}

Suppose then [w]B = [-2;4], what then is [w]s?

This is a fairly simple question but the confusion stems from the fact that I am still fuzzy about how I should determine the direction of the change of coordinate of the basis B. From which coordinates to which does the basis b purports the movement to be?
If I know the basis B maps the coordinates from, for instance, a to b then I could set the equation up as [x]a = Bab[x]b
 
  • #4
HallsofIvy said:
The definition of "u, v are Linearly Independent" is that "if au+ bv= 0 then a= b= 0". Applied here, that would be a[1; -4; 0]+ b[0; 3; 1]= [a; -4a+ 3b; b]= [0; 0; 0] which tells you that a= 0; -4a+ 3b= 0; b= 0. The first and third equations tell you everything you need to know, don't they?

negation said:
How do I know a[1;-4;0]+b[0;3;1] =[0;0;0]?

You are wanting to show those two vectors are linearly independent. What about Hall's explanation don't you understand?
 
  • #5
LCKurtz said:
You are wanting to show those two vectors are linearly independent. What about Hall's explanation don't you understand?

Hi Kurtz,

That wasn't what I wanted. I read my notes and it says that the basis is linearly independent.
Where did the zero vector came from?
 
  • #6
negation said:

Homework Statement



Find the basis for the subspace 4x+y-3z


The Attempt at a Solution



I found that the basis is {[1;-4;0],[0;3;1]}. How do I know if it is linearly independent? I know that the mathematical definition of what LI is but how can it be applied to show in this case?

HallsofIvy said:
The definition of "u, v are Linearly Independent" is that "if au+ bv= 0 then a= b= 0". Applied here, that would be a[1; -4; 0]+ b[0; 3; 1]= [a; -4a+ 3b; b]= [0; 0; 0] which tells you that a= 0; -4a+ 3b= 0; b= 0. The first and third equations tell you everything you need to know, don't they?

negation said:
How do I know a[1;-4;0]+b[0;3;1] =[0;0;0]?

LCKurtz said:
You are wanting to show those two vectors are linearly independent. What about Hall's explanation don't you understand?

negation said:
Hi Kurtz,

That wasn't what I wanted. I read my notes and it says that the basis is linearly independent.
Where did the zero vector came from?

But you don't know it is a basis until you show the vectors are linearly independent. And that is what you asked, as quoted in red above. Halls explained how you show that, and his explanation, including the definition of linear independence, shows why you set the linear combination equal to zero.
 
  • #7
LCKurtz said:
But you don't know it is a basis until you show the vectors are linearly independent. And that is what you asked, as quoted in red above. Halls explained how you show that, and his explanation, including the definition of linear independence, shows why you set the linear combination equal to zero.


I don't know what was I thinking but this part clicked. Thanks.

Second part, anyone?
 

Related to Basis for Subspace: Find & Check LI

1. What is the basis for subspace?

The basis for subspace is a set of linearly independent vectors that span the entire subspace. This means that any vector in the subspace can be written as a linear combination of the basis vectors.

2. How do you find the basis for a subspace?

To find the basis for a subspace, you need to find a set of linearly independent vectors that span the subspace. This can be done by finding the pivot columns in the reduced row echelon form of the subspace's matrix representation.

3. Why is it important to check for linear independence when finding the basis for a subspace?

Checking for linear independence ensures that the basis vectors chosen can uniquely describe any vector in the subspace. If the basis vectors are not linearly independent, there will be redundant information and the basis will not be able to fully span the subspace.

4. Can there be multiple bases for the same subspace?

Yes, there can be multiple bases for the same subspace. As long as the basis vectors are linearly independent and span the subspace, they can be considered a basis for that subspace.

5. How can you check if a set of vectors is a basis for a subspace?

To check if a set of vectors is a basis for a subspace, you can use the following criteria: (1) the vectors must span the subspace, (2) the vectors must be linearly independent, and (3) the number of vectors in the set must be equal to the dimension of the subspace.

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