N(A) and R(A) in terms of their basis

In summary, the conversation discusses the correct format for expressing the null space and row space of a matrix, including whether to use curly brackets or square brackets and whether to give the answer in terms of basis vectors or as a basis set. The correct format is to either state that all vectors in the null space are of the form x1[v1] + x2[v2] or to give a basis for the null space as {v1, v2}.
  • #1
DryRun
Gold Member
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4

Homework Statement


The matrix A =
1 1 1 1
-1 0 1 0
1 2 3 2

Express null space and row space of A in terms of their basis vectors.

2. The attempt at a solution

I have found the null space to be: x3 [1 -2 1 0]^T + x4 [0 -1 0 1]^T.

But my problem is how do i write the final answer correctly? Should i just write the answer as above? Or should i just write it this way: [1 -2 1 0]^T and [0 -1 0 1]^T

I did a search online and ended up with this way to present the solution, but there are so many variations, I'm confused.
{[1 -2 1 0]^T, [0 -1 0 1]^T}.

Which is the correct established answer format?

For the row space, i gave the answer like this:
[ 1 1 1 1] and [0 1 2 1]

Or should it be like this?: {[ 1 1 1 1], [0 1 2 1]}
 
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  • #2
The problem says to "Express the null space of A in terms of its basis vectors.
So I would say you can give the answer in either of two ways:
1) "All vectors in the null space of A are of the form [itex]x_1\begin{bmatrix}1 \\ -2 \\ 1 \\ 0\end{bmatrix}+ x_2\begin{bmatrix}0 \\ -1 \\ 0 \\ 1\end{bmatrix}[/itex]"
or
2) "A basis for the null space is [itex]\{\begin{bmatrix}1 \\ -2\\ 1\\ 0 \end{bmatrix}, \begin{bmatrix}0 \\ -1 \\ 0 \\ 1\end{bmatrix}\}[/itex]".

But the words explaining what you answer means are as important as your vectors.
 
  • #3
Thanks for your help, HallsofIvy. I will keep your advice in mind for my exams.
 
  • #4
Yep- actually writing out full sentence answers is likely to send your teacher into shock!
 
  • #5
You can also say that the null space is span{(v1), (v2)}.
 

FAQ: N(A) and R(A) in terms of their basis

What is the difference between N(A) and R(A)?

N(A), or the null space, is the set of all vectors in the domain of a linear transformation that are mapped to the zero vector in the range. R(A), or the range, is the set of all possible output vectors of a linear transformation.

How are the bases of N(A) and R(A) related?

The basis of N(A) is a set of linearly independent vectors that span the null space, while the basis of R(A) is a set of linearly independent vectors that span the range. These two bases are related by the rank-nullity theorem, which states that the dimension of the null space plus the dimension of the range will always equal the dimension of the domain.

Can N(A) and R(A) have the same basis?

No, N(A) and R(A) cannot have the same basis. This is because the basis of N(A) consists of all vectors that are mapped to the zero vector, while the basis of R(A) consists of all possible output vectors. Since the zero vector cannot be a part of R(A), the two bases cannot be the same.

How do the bases of N(A) and R(A) change under a change of basis?

The bases of N(A) and R(A) remain unchanged under a change of basis. This is because the basis vectors represent the fundamental structure of the vector space, and changing the basis does not change this fundamental structure.

Can the basis of N(A) or R(A) be empty?

Yes, the basis of N(A) or R(A) can be empty if the dimension of the null space or range is zero. This means that there are no linearly independent vectors that span the null space or range, and thus the basis is empty. This can happen when the linear transformation is trivial, such as the zero transformation.

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