Linear Algebra question: finding bases

In summary, the problem involves showing that the set {A_1, A_2, A_3, A_4} is a basis for the vector space M_2 R. This requires proving that the set is linearly independent and spans the space, or that it contains 4 vectors, which is equivalent to the dimension of M_2 R. There may be a theorem that can be used to simplify the proof, but if not, it can be easily shown by reducing to 4 equations in 4 unknowns and proving that the coefficient matrix has a non-zero determinant.
  • #1
kdawghomie
3
0

Homework Statement



The problem states:

Let

A_1 = [-1 1] , A_2 = [1 3]
...[0 1]...[-1 0]

A_3 = [1 0] , A_4 = [0 -1]
...[1 2]...[2 3]

Show that {A_1, A_2, A_3, A_4} is a basis for M_2 R.

The attempt at a solution

I'm very confused about this problem. I understand that to show {A_1, ..., A_4} is a basis, I must show 1.) the set is linearly independent, and 2.) it is a spanning set; however, I know there is a less complicated way instead of going through these 2 steps. I'm really not sure what the "easy" way is for doing this problem... it hints that there is a Thm that will help solve the problem, but I have found none that fit the bill. Can someone please help me with all this?
 
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  • #2
A basis, for a vector space of dimension n, satisfies 3 properties:
1) it spans the space
2) it is independent
3) it contains n vectors.

If any two of those are true the third must be. If you know, or are given, that M_2 R is a 4 dimensional vector space, that might be the theorem you are referring to. Since this set contains 4 matrices, (3) above is clearly satisfied and you only need to prove either (1) or (2), not both.

If you do not know that the M_2 R is 4 dimensional, then you will need to prove both (1) and (2), and, honestly, they are not that difficult! Both reduce to 4 equations in 4 unknowns and you really only need to show that those equations have a unique solution- which is true if the 4 by 4 coefficient matrix does not have 0 determinant. It would probably take you less time than waiting for a response on the internet.
 

Related to Linear Algebra question: finding bases

1. What is the definition of a basis in linear algebra?

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

2. How do you find the basis of a vector space?

To find the basis of a vector space, you can use a few methods. One way is to use Gaussian elimination to reduce the vectors to their row echelon form and then select the pivot columns as the basis. Another method is to use the Gram-Schmidt process to orthogonalize the vectors and then select the resulting orthogonal vectors as the basis.

3. Can a vector space have more than one basis?

Yes, a vector space can have multiple bases. This is because there are often multiple sets of linearly independent vectors that can span the same vector space.

4. How many vectors are in a basis for a given vector space?

The number of vectors in a basis for a given vector space is equal to the dimension of the vector space. For example, a basis for a 3-dimensional vector space would have 3 vectors.

5. Can a vector be a part of more than one basis for a given vector space?

No, a vector can only be a part of one basis for a given vector space. This is because a basis must be linearly independent, meaning that no vector in the basis can be written as a linear combination of the other vectors in the basis.

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