Show that non-zeros rows in REF are linearly independent

In summary: This would then have your property that all the elements below the leading entries are zero. But we don't usually bother writing the zero row.To summarize, we can say that in row echelon form, the nonzero rows have the property that all the elements in a column to the left of the leading entry are zero. In summary, the rows of a matrix in row echelon form are linearly independent, as they have the property that all the elements in a column to the left of the leading entry are zero. This means that the nonzero rows of any matrix in row echelon form are also linearly independent.
  • #1
negation
818
0

Homework Statement

Given

2 1 1 0
0 0 1 1
0 0 0 3(i) Show that the rows of A are linearly independent.
(ii) Show that the nonzero rows of any matrix in row echelon form are linearly independent.

The Attempt at a Solution



i)
REF gives

1 0 0 | 0
0 1 0 | 0
0 0 1 | 0
0 0 0 | 0
x1 = x2 = x3 =x4 = 0

The solution set is non-trivial due to the row of zeroes and the system is linearly dependent. The rank is 3 and the basis is {(1,0,0),(0,1,0),(0,0,1)}

ii) Can someone give me a step by step guidance on this part?
 
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  • #2
Suppose a matrix is in row echelon form. Consider any nonzero row of the matrix. What can you say about that row which is not true of any row below it?
 
  • #3
jbunniii said:
Suppose a matrix is in row echelon form. Consider any nonzero row of the matrix. What can you say about that row which is not true of any row below it?


For a matrix in REF, the non-zero row with the entry aij is to the left of the non-zero row with the entry a2ij to the left of entry a3ijto the left of a4ij and so on to anij.
 
  • #4
##a_{ij}## refers to the entry in the ##i##th row and ##j##th column of the matrix. Where is the element ##a_{3ij}##?
 
  • #5
LCKurtz said:
##a_{ij}## refers to the entry in the ##i##th row and ##j##th column of the matrix. Where is the element ##a_{3ij}##?
For a matrix in REF, the non-zero row with the entry aaa is to the left of the non-zero row with the entry abb to the left of entry acc to the left of add and so on to ann

Tell me if there's a better way of sub-scripting the entries.

Edit: I could have been confused by your question.

a3ij is the entry located at the 3rd row 3rd column.
 
  • #6
negation said:
For a matrix in REF, the non-zero row with the entry aaa is to the left of the non-zero row with the entry abb to the left of entry acc to the left of add and so on to ann

Tell me if there's a better way of sub-scripting the entries.
No, that's perfectly good. But you are not using it below.

Edit: I could have been confused by your question.

a3ij is the entry located at the 3rd row 3rd column.
According to what you said above, the "entry located at the 3rd row 3rd column" would be a33, NOT a3ij.
 
  • #7
negation said:
Edit: I could have been confused by your question.

a3ij is the entry located at the 3rd row 3rd column.

It's the notation that is confusing you. Three subscripts makes no sense. The entry in the third row and third column is ##a_{33}##. The element to its right is ##a_{34}##. The element to the right of ##a_{ij}## is ##a_{i,j+1}##.
 
  • #8
HallsofIvy said:
No, that's perfectly good. But you are not using it below.


According to what you said above, the "entry located at the 3rd row 3rd column" would be a33, NOT a3ij.

LCKurtz said:
It's the notation that is confusing you. Three subscripts makes no sense. The entry in the third row and third column is ##a_{33}##. The element to its right is ##a_{34}##. The element to the right of ##a_{ij}## is ##a_{i,j+1}##.

Let's stick to " For a matrix in REF, the non-zero row with the entry aaa is to the left of the non-zero row with the entry abb to the left of entry acc to the left of add and so on to ann"
 
  • #9
negation said:
Let's stick to " For a matrix in REF, the non-zero row with the entry aaa is to the left of the non-zero row with the entry abb to the left of entry acc to the left of add and so on to ann"

You can stick to that if you wish, but I don't have any idea what it means for one row to be to the left of another row.
 
  • #10
negation said:
Let's stick to " For a matrix in REF, the non-zero row with the entry aaa is to the left of the non-zero row with the entry abb to the left of entry acc to the left of add and so on to ann"

How can one row be to the right of another?

Anyway, would it not be much easier just to say that all the elements in column ##i##, lying below ##a_{ii}##, are zero. REF is like an upper-triangular matrix but possibly with some zero rows inserted.
 
  • #11
LCKurtz said:
You can stick to that if you wish, but I don't have any idea what it means for one row to be to the left of another row.

Ray Vickson said:
How can one row be to the right of another?

Anyway, would it not be much easier just to say that all the elements in column ##i##, lying below ##a_{ii}##, are zero. REF is like an upper-triangular matrix but possibly with some zero rows inserted.

Alright I was sloppy and careless with words.

The matrix has entries aaa, abb ...ann and has zeroes everywhere else.
 
  • #12
negation said:
Alright I was sloppy and careless with words.

The matrix has entries aaa, abb ...ann and has zeroes everywhere else.

I suppose you mean those are nonzero, which you should state if that's what you mean. (That "sloppy and careless with words" thing again). Even so, does that describe this matrix?$$
\begin{bmatrix}
1&0&0&0\\
0&0&1&0\\
0&0&0&1
\end{bmatrix}$$Here both ##a_{22}## and ##a_{33}## are ##0##.
 
  • #13
negation said:
Alright I was sloppy and careless with words.

The matrix has entries aaa, abb ...ann and has zeroes everywhere else.

The USUAL form of REF does not conform to what you say. A matrix like
[tex] A = \begin{bmatrix}
1 & 2 & 0 & -1 \\
0 & 3 & 1 & 1 \\
0 & 0 & 0 & 2
\end{bmatrix}
[/tex]
is a perfectly good REF. As I had said already, you can think of ##A## as arising from an upper-triangular matrix
[tex] B = \begin{bmatrix}
1 & 2 & 0 & -1 \\
0 & 3 & 1 & 1 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 2
\end{bmatrix}
[/tex]
by removing the zero row.
 

1. What is REF?

REF stands for Reduced Echelon Form, which is a special form of a matrix where all the leading coefficients (first non-zero element) of each row are equal to 1 and all the elements below the leading coefficients are equal to 0.

2. How do you show that non-zero rows in REF are linearly independent?

To show that non-zero rows in REF are linearly independent, you need to perform elementary row operations on the matrix until it is in REF. Then, you can examine the leading coefficients of each row and check if they are all equal to 1. If they are, then the non-zero rows are linearly independent.

3. What are elementary row operations?

Elementary row operations are operations that can be performed on a matrix to transform it into REF. These include multiplying a row by a non-zero scalar, switching the positions of two rows, and adding a multiple of one row to another row.

4. Why is it important to show that non-zero rows in REF are linearly independent?

It is important to show that non-zero rows in REF are linearly independent because it is a key step in determining the rank of a matrix. The rank of a matrix is the number of linearly independent rows or columns, and it has many applications in fields such as engineering, economics, and computer science.

5. What is the significance of linear independence in a matrix?

Linear independence is significant in a matrix because it allows us to determine if the rows or columns of a matrix can be written as linear combinations of each other. This information is useful in solving systems of equations, finding bases for vector spaces, and in many other mathematical applications.

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