I have a pivot in every row, but it is still not linearly independent

In summary, the matrix A is not linearly independent because there are pivots in every row, which means that the nullspace of the matrix is not just the zero vector.
  • #1
flyingpig
2,579
1

Homework Statement



I need to argue this properly

Let's say I have a matrix A and rref(A) is given as

[tex]\begin{bmatrix}
1 & 0&-1 \\
0& 1 & -1
\end{bmatrix}[/tex]

Since I have a pivot in every row, why isn't this linearly independent? Don't give me other arguments like "because there are more vectors than entires", "it's not a good basis for R^2".
 
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  • #2
the column vectors are clearly linearly dependent as the 3rd can be written as a linear combo of the first 2
c3 = -c1 -c2
 
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  • #3
I don't need other counterarguments. I want to know why pivots in every row does not mean linear indepedence
 
  • #4
Why isn't what linearly independent? You need to be more specific about what you're describing as linearly independent/dependent. The rows, taken as vectors in R3, are clearly linearly independent (neither one is a multiple of the other). The column vectors, taken as vectors in R2, are clearly linearly dependent, since there are three of them.

Let's call your matrix A. If your matrix represents the equation Ax = 0, where x is a vector in R3, then there are nontrivial solutions for x. This is the same as saying that the nullspace of A is not just the zero vector.
 
  • #5
flyingpig said:
I don't need other counterarguments. I want to know why pivots in every row does not mean linear indepedence

it wasn't a counter-argument, it was an observation of the linear dependence of the column vectors

As Marks says, you need to be clear about what you are actually asking, as your question does not seem well formed.

The row vectors are clearly linearly independent.

If you are trying to solve for a point in R^3, as in the solution Ax=0 , then each row acts as a constraint (geometrically it represents a plane of allowable solutions in R^3)

as you have two non-parallel planes, their intersection is a line of points that satisfy both constraints - giving infinite solutions...
 
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  • #6
I got mixed up with row vectors and column vectors, that's the answer I was looking for.

I still don't understand what is a row vector, I still think the columns are defined as x, y, z, and so on continuously on the vertical
 
  • #7
If you don't know the difference between rows and columns in a matrix you need to talk to your teacher!

You start of by asking "Why isn't this independent" without any clear statement of what "this" is. Grammatically, you would be referring to the matrix, but "independent" applies to a set of vectors, not a matrix.

If you are referring to the columns of the matrix as vectors,
[tex]\begin{bmatrix}1 \\ 0\end{bmatrix}[/tex][tex]\begin{bmatrix}0 \\ 1\end{bmatrix}[/tex][tex]\begin{bmatrix}-1 \\ -1 \end{bmatrix}[/tex]
They are dependent because any set of 3 2-dimensional vectors (any set of more than n n-dimensional vectors) must be dependent. The pivots have nothing to do with that!

If you are talking about the rows of the matrix as vectors,
[itex]\begin{bmatrix}1 & 0 & -1\end{bmatrix}[/itex], [itex]\begin{bmatrix}0 & 1 & -1\end{bmatrix}[/itex]
then they are independent.
 

FAQ: I have a pivot in every row, but it is still not linearly independent

1. What does it mean to have a pivot in every row?

Having a pivot in every row means that every row in a matrix has a leading (non-zero) entry in the column that is used to eliminate variables in the process of solving a system of linear equations. This is an important concept in determining the linear independence of a set of vectors.

2. Why is having a pivot in every row not enough for linear independence?

While having a pivot in every row is a necessary condition for linear independence, it is not sufficient. In order for a set of vectors to be linearly independent, the pivots must also be in different columns. This ensures that no vector can be written as a linear combination of the others.

3. Can a matrix have a pivot in every row and still have linearly dependent rows?

Yes, it is possible for a matrix to have a pivot in every row and still have linearly dependent rows. This can happen if the pivots are in the same columns, meaning that some rows can be written as linear combinations of others.

4. How can I test for linear independence if a matrix has a pivot in every row?

If a matrix has a pivot in every row, you can test for linear independence by checking if the pivots are in different columns. If they are, then the set of vectors is linearly independent. If not, then the set is linearly dependent.

5. Can a set of vectors be linearly independent if there are no pivots in the matrix?

No, a set of vectors cannot be linearly independent if there are no pivots in the matrix. This means that the matrix has either all zeros or all non-leading entries, indicating that all the variables can be eliminated and the system of equations has infinitely many solutions. In order for a set of vectors to be linearly independent, there must be at least one pivot in the matrix.

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