Determine a basis for kernel/nullspace

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To determine a basis for the kernel of the matrix A, Gaussian elimination is used to find the nullspace. The discussion emphasizes that a basis consists of unordered vectors, and both provided bases are valid as they span the same nullspace. It clarifies that including parameters like s and t indicates arbitrary elements of the nullspace rather than a basis itself. The basis vectors uniquely define the subspace, and any nonzero multiple of these vectors can also serve as a basis. Understanding these concepts is crucial for correctly applying the Gram-Schmidt process and recognizing the nature of basis vectors.
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Homework Statement


[/B]
A=##\begin{bmatrix}
1 & 2 & 3 \\
4 & 8 & 12
\end{bmatrix}##

Question: Determine a basis for ker(A).

Homework Equations


Ker(A)=##\begin{bmatrix}
1 & 2 & 3& |&0 \\
4 & 8 & 12& |&0
\end{bmatrix}##

(And reduce with gaussian elimination)

The Attempt at a Solution


(Sorry for no attempt on LaTeX here, it's my first time trying to use it at all above.)

Some background information, i am revisiting linear algebra and I were doing gram-schmidt process and got a totally different answer than the textbook, however i am confident i did not make a mistake during the actual gram-schmidt.
Then it occurred to me that i must have chosen a different basis than the textbook, which made me unsure in what i recall and know about the basis for the kernel. I couldn't really find any straight forward information about it in my textbook or with a few google searches, so now I've gotten caught up in my own minor insecurities in basic details.

A easy example below to illustrate my point, are both Basis #1 and Basis #2 correct (i just realized that i wrote base on the paper...)? They would of course lead to two very different orthogonal basis when using gram-schmidt, but both would be orthogonal nonetheless.

My reasoning behind them being equally correct is that there is no (to me) intuitive "basis vector 1 and basis vector 2" as it would be for example unit vectors. Still, the span should be independent of the order in the "set" anyway if i am not wrong? I.e. i would still reach all the points regardless of the order.

b2AyL0a.jpg
 

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A basis is an unordered set of vectors. So the two things you wrote relate to the same basis, which is indeed a basis for the null space.

Also, you don't write the s and t in writing the basis. Writing the s and t gives an arbitrary element of the null space, not a basis. In this case a basis is just two purely numeric vectors.
 
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andrewkirk said:
A basis is an unordered set of vectors. So the two things you wrote relate to the same basis, which is indeed a basis for the null space.

Also, you don't write the s and t in writing the basis. Writing the s and t gives an arbitrary element of the null space, not a basis. In this case a basis is just two purely numeric vectors.
Great, thanks.

That's very true, i think i tried to make it overly clear with the "order" by keeping the parameters.

Thanks for clarifying!
 
Bobman said:
Great, thanks.

That's very true, i think i tried to make it overly clear with the "order" by keeping the parameters.

Thanks for clarifying!
The basis vectors are the things that completely define this subspace. Every vector in the nullspace is a linear combination of these two vectors, so if ##\vec v \in Null(A)##, then ##\vec v = s<-2, 1, 0> + t<-3, 0, 1>##.
That's where the parameters come in, not when you are just listing the vectors that form a basis. Note that any nonzero multiple of either vector would also consitute a basis.
In a set, the order of the set elements doesn't matter.
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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