Discovering the Basis, Rank, and Nullity of T_A: Linear Algebra Explained

In summary, for the given linear transformation T with matrix A, we need to find a basis for the kernel and image of T and determine the rank and nullity of T. To find the kernel, we need to find the null space of A by row reducing it. The basis of A will be the rank of T, which is 2. The dimension of the kernel (nullity) of T is also 2. The number of independent rows in A is also the rank of A, which is 2. The rank of the kernel is the number of linearly independent vectors formed from AX = 0. And no, I am not an orthodontist.
  • #1
stunner5000pt
1,461
2
Fpr the matrix find a basis for hte kernel and image of [itex} T_{A} [/itex] and find the rank and nullity of [itex] T_{A} [/itex]
T is a linear transformation


[tex] \left(\begin{array}{cccc} 2&1&-1&3 \\ 1&0&3&1 \\ 1&1&-4&2 \end{array} \right) [/tex]

the kernel of T simply means to find the null space of A right?
so when i row reduce i get
[tex] \left(\begin{array}{cccc} 1&0&3&1 \\ 0&1&-7&0 \\ 0&0&0&0 \end{array} \right) [/tex]

so do i simply find a 3x1 line matrix X such taht AX = 0
The image means something to do iwth the solution... but there is no augmented form given here... is there??

the basis of A will be the rank T right? Is base A = 2?? So the rank of T = 2?
the dimensio of the kernel is T is nullity of T... but i need to find the basis for the kernel first
 
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  • #2
The _rank_ of A will be the rank of T. Otherwise you are correct, what you need to do is find all the vectors x such that Ax = 0, from which you can extract a basis.
 
  • #3
ok s oteh rank of kernel of T is 2

what about he nullity, though?? SO basically it asks how many vectors are forming the basis of th kernel?
 
  • #4
No, the _dimension_ of the kernel of T is 2. That _is_ the nullity.
 
  • #5
ok ok
so the number of independant rows in A: is the rank of A and that is 2
that is the tank of Ta yes?

also the rank of the kernel is the number of linearly independant vecotrs that can be formed from AX = 0 right

p.s. are you an orthodontist?
 

1. What is the basis of T_A?

The basis of T_A is the set of all linearly independent vectors that span the range of T_A. In other words, it is the set of vectors that can be used to create any vector in the range of T_A through linear combinations.

2. How is the rank of T_A determined?

The rank of T_A is equal to the number of linearly independent columns in the matrix representation of T_A. This can also be seen as the dimension of the range of T_A.

3. What is the significance of the rank of T_A?

The rank of T_A is a measure of the dimension of the range of T_A, which represents the number of linearly independent columns or rows in the matrix representation of T_A. It is an important concept in linear algebra as it helps us understand the properties and behavior of linear transformations.

4. How is the nullity of T_A calculated?

The nullity of T_A is equal to the dimension of the null space of T_A, which is the set of all vectors that are mapped to the zero vector by T_A. It can be calculated by subtracting the rank of T_A from the number of columns in the matrix representation of T_A.

5. Why is it important to understand the basis, rank, and nullity of T_A?

The basis, rank, and nullity of T_A provide valuable information about the properties and behavior of linear transformations. They help us understand the dimensions of the range and null space, and the number of linearly independent vectors that are necessary to create all vectors in the range. This knowledge can be applied in various fields, such as computer science, physics, and engineering.

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