I don't understand the rank of a matrix

In summary, the rank of a matrix is the number of linearly independent rows in the matrix and can be found by performing Gaussian elimination and counting the number of non-zero rows in the resulting matrix. This can also be interpreted as the number of columns that cannot be written as a linear combination of each other.
  • #1
mr_coffee
1,629
1
Hello everyone, can someone explain to me what the rank of a matrix is?
I have the following:
2 3 -2
2 6 0
-4 0 0
Rank = 3;

0 2 0 0
0 0 0 -4
0 0 0 0
9 0 0 0
rank = 3;


1 2
6 -3
Rank = 2;

I don't get it! any help would be great!
 
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  • #2
Hey,

The rank of a matrix is the number of linearly independent rows in the matrix.

You can find the rank by performing Gaussian elimination. The rank will then be the number of non-zero rows in the resulting matrix.
 
  • #3
To compute the rank of a matrix, do the following.

1) Let [tex] A [/tex] be a [tex] m\times n[/tex] matrix.
2) Perform gaussian-elimination on [tex] A [/tex]
3) Count the number of non zero columns. This number is the rank of the matrix.

We'll start with your first example.
1) [tex] A = \left[ \begin{array}{ccc}2 & 3 & -2 \\2 & 6 & 0 \\-4 & 0 & 0 \\\end{array}\right] [/tex]

2) Perform the gaussian-elimination on [tex] A [/tex]
[tex] A' = \left[ \begin{array}{ccc}1 & 0 & 0 \\0 & 1 & 0 \\0 & 0 & 1 \\\end{array}\right] [/tex]

3) Now we count the number of non-zero columns:
[tex] A' = \left[ \begin{array}{ccc}(1) & 0 & 0 \\0 & (1) & 0 \\0 & 0 & (1) \\\end{array}\right] [/tex]

Rank = 3

----
Now, what does the rank mean? Well the rank of a matrix let's you know the number of columns that cannot be written as a linear combination of each other.

If you consider [tex] A' [/tex] to be a matrix of vectors, we would have the following column vectors.

[tex] \vec{V_1} = (1,0,0) [/tex]
[tex] \vec{V_2} = (0,1,0) [/tex]
[tex] \vec{V_3} = (0,0,1) [/tex]

These vectors are ALL linearly independent of each other. Which means that the column vectors in [tex] A [/tex] are all linearly independent of each other.
 
  • #4
Just don't forget that the rank only tells you the number of independent columns. If you are trying to find the spanning set, you must go back to the ORIGINAL matrix.
 
  • #5
Awesome! thanks a lot guys! good explanation! :biggrin:
 

What is the rank of a matrix?

The rank of a matrix is the maximum number of linearly independent rows or columns in the matrix. In other words, it is the number of dimensions in the vector space spanned by the rows or columns of the matrix.

How is the rank of a matrix determined?

The rank of a matrix can be determined by performing row operations on the matrix and counting the number of non-zero rows in the reduced row echelon form. The number of non-zero rows will be the same as the rank of the matrix.

Why is the rank of a matrix important?

The rank of a matrix is important because it provides information about the dimension of the vector space spanned by the rows or columns of the matrix. It can also help in solving systems of linear equations and in understanding the properties of the matrix.

Can the rank of a matrix be greater than the number of rows or columns?

Yes, the rank of a matrix can be greater than the number of rows or columns. This means that there are linearly dependent rows or columns in the matrix and they can be expressed as a combination of other rows or columns.

What does it mean if the rank of a matrix is zero?

If the rank of a matrix is zero, it means that all the rows and columns of the matrix are linearly dependent and the matrix has no non-zero elements. This also means that the determinant of the matrix is zero and the matrix is not invertible.

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