Linear algebra and linearly independence

In summary, the conversation discusses determining linear independence of three vectors in R^(2x2). The method involves setting a linear combination of the vectors equal to 0 and showing that this can be satisfied without all coefficients being 0. If this is possible, the vectors are dependent, and one can be written as a linear combination of the others.
  • #1
Niles
1,866
0

Homework Statement


I have three vectors in R^(2x2):

(1 0 , 0 1) (That is "1 0" horizontal first line, and "0 1" horizontal second line), (0 1, 0 0) and (0 0, 1 0).

I have to determine if they are linear independent or not. I know how to do it in R^(2x1), but not in R^(2x2). What's the method?
 
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  • #2
Are these matrices?
 
  • #3
It's the same thing

If

a( (1,0),(0,1) ) + b( (0,1),(0,0) ) + c( (0,0), (1,0) ) = 0 (0 being ( (0,0),(0,0) )
then

( (a,b),(c,a) ) = ( (0,0),(0,0) ) so comparing positions, we get that a=b=c=0

(this assumes I interpreted R^(2x2) correctly, but I think I did)
 
  • #4
Yes, these are matrices.

So the example is linearly independent, because they cannot be written as a linear combination?

If we take a new example: a(1,0)(0,1) + b(0,1)(0,0) + c(2,3)(0,2) = 0.

Then we get:

(a + 2c, b+3c)(0, a + 2c) = 0 so it is linearly dependent?
 
  • #5
You almost "tricked" me- I misread "linearly dependent" as "linearly independent! Just setting the linear combination equal to 0, and adding is not sufficient. You have to specifically show that this can be satisfied without a, b, c all being 0. Here, you should also show that a+ 2c= 0, and b+ 3c= 0 are true if a= -2c and b= -3c. In particular, if c= 1, a= -2, b= -3, you have
[tex]-2\left[\begin{array}{cc}1 & 0 \\ 0 & 1\end{array}\right]- 3\left[\begin{array}{cc}0 & 1 \\ 0 & 0\end{array}\right]+ \left[\begin{array}{cc}2 & 3 \\0 & 2\end{array}\right]= \left[\begin{array}{cc}0 & 0 \\ 0 & 0 \end{array}\right][/tex]
Because it is possible to get the zero matrix without the coefficients all being 0, they are dependent. That is, by the way, equivalent to saying one of the matrices can be written as a linear combination of the other two- here, just move the first two matrices to the right of the equation.
 

Related to Linear algebra and linearly independence

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with the study of linear equations and their properties. It involves the use of vector spaces, matrices, and systems of linear equations to solve problems related to lines, planes, and higher dimensional spaces.

2. What is the difference between linearly independent and linearly dependent vectors?

Linearly independent vectors are those that cannot be expressed as a linear combination of other vectors in the same space. In other words, they are not redundant and add new information to the space. On the other hand, linearly dependent vectors are those that can be expressed as a linear combination of other vectors in the same space. They are considered redundant and do not add new information to the space.

3. How do you determine if a set of vectors is linearly independent?

A set of vectors is linearly independent if none of the vectors can be written as a linear combination of the others. This means that the only solution to the equation c1v1 + c2v2 + ... + cnvn = 0 is when all the coefficients c1, c2, ..., cn are equal to 0. In other words, the only way for the vector equation to equal 0 is if all the vectors are multiplied by 0.

4. What is the importance of linearly independent vectors in linear algebra?

Linearly independent vectors are important because they form a basis for a vector space. This means that any vector in the space can be expressed as a unique linear combination of these vectors. They also help to determine the dimension of a vector space and are used in various applications such as solving systems of linear equations and performing transformations.

5. Can a set of linearly dependent vectors be linearly independent?

No, a set of linearly dependent vectors cannot be linearly independent. If a set of vectors is linearly dependent, it means that at least one of the vectors can be expressed as a linear combination of the others. This implies that the set is not linearly independent, as there exists a non-trivial solution to the equation c1v1 + c2v2 + ... + cnvn = 0.

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