Rank of a Matrix
The rank of a matrix is equal to the number of linearly independent rows (or columns) in it. Hence, it cannot more than its number of rows and columns. For example, if we consider the identity matrix of order 3x3, all its rows (or columns) are linearly independent and hence its rank is 3.
Let us learn more about the rank of a matrix along with its mathematical definition and let us see how to find the rank of the matrix along with examples.
What is the Rank of a Matrix?
The rank of a matrix is the order of the highest ordered nonzero minor. Let us consider a nonzero matrix A. A real number 'r' is said to be the rank of the matrix A if it satisfies the following conditions:
 every minor of order r + 1 is zero.
 There exist at least one minor of order 'r' that is nonzero.
The rank of a matrix A is denoted by ρ (A). Here, "ρ" is a Greek letter that should be read as "rho". So ρ (A) should be read as "rho of A" (or) "rank of A".
How to Find the Rank of a Matrix?
Here are the steps to find the rank of a matrix A.
 Find the determinant of A (if A is a square matrix). If det (A) ≠ 0, then the rank of A = order of A.
 If either det A = 0 (in case of a square matrix) or A is a rectangular matrix, then see whether there exist any minor of maximum possible order is nonzero. If there exists such nonzero minor, then rank of A = order of that particular minor.
 Repeat the above step if all the minors of the order considered in the above step are zeros and then try to find a nonzero minor of order that is 1 less than the order from the above step.
Here is an example.
Example: Find the rank of the matrix ρ (A) if A = \(\left[\begin{array}{lll}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9
\end{array}\right]\).
Solution:
A is a square matrix and so we can find its determinant.
det (A) = 1 (45  48)  2 (36  42) + 3 (32  35)
= 3 + 12  9
= 0
So ρ (A) ≠ order of the matrix. i.e., ρ (A) ≠ 3.
Now, we will see whether we can find any nonzero minor of order 2.
\(\left\begin{array}{ll}
1 & 2 \\ \\
4 & 5
\end{array}\right\) = 5  8 = 3 ≠ 0.
So there exists a minor of order 2 (or 2x2) which is nonzero. So the rank of A, ρ (A) = 2.
Rank of a Matrix Using Echelon Form
In the above example, what if the first minor of order 2x2 that we found was zero? We had to find all possible minors of order 2x2 until we get a nonzero minor to make sure that the rank is 2. This process may be tedious if the order of the matrix is a bigger number. To make the process of finding the rank of a matrix easier, we can convert it into Echelon form. A matrix 'A' is said to be in Echelon form if it is either in upper triangular form or in lower triangular form. We can use elementary row/column transformations and convert the matrix into Echelon form.
A row (or column) transformation can be one of the following:
 Interchanging two rows.
 Multiplying a row by a scalar.
 Multiplying a row by a scalar and then adding it to the other row.
To find the rank of a matrix:
 Convert the matrix into Echelon form using row/column transformations.
 Then the rank of the matrix is equal to the number of nonzero rows in the resultant matrix.
A nonzero row of a matrix is a row in which at least one element is nonzero.
Example: Find the rank of the matrix A = \(\left[\begin{array}{lll}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9
\end{array}\right]\) (the same matrix as in the previous example) by converting it into Echelon form.
Solution:
Given matrix is, A = \(\left[\begin{array}{lll}
1 & 2 & 3 \\
4 & 5 & 6 \\
7 & 8 & 9
\end{array}\right]\).
Apply R₂ → R₂  4R₁ and R₃ → R₃  7R₁, we get:
\(\left[\begin{array}{lll}
1 & 2 & 3 \\
0 & 3 & 6 \\
0 & 6 & 12
\end{array}\right]\)
Now, we apply R₃ → R₃  2R₂, we get:
\(\left[\begin{array}{lll}
1 & 2 & 3 \\
0 & 3 & 6 \\
0 & 0 & 0
\end{array}\right]\)
Now it is in Echelon form and so now we have to count the number of nonzero rows.
The number of nonzero rows = 2 = rank of A.
Therefore, ρ (A) = 2.
Note that we had got the same answer when we calculated the rank using minors.
Rank of a Matrix Using Normal Form
If a rectangular matrix A can be converted into the form \(\left[\begin{array}{ll}
Iᵣ & 0 \\ \\
0 & 0
\end{array}\right]\) by using the elementary row transformations, then A is said to be in normal form. Here, Iᵣ is the identity matrix of order "r" and when A is converted into the normal form, its rank is, ρ (A) = r. Here is an example. Converting into normal form is helpful in determining the rank of a rectangular matrix. But it can be used to find the rank of square matrices also.
Example: Find the rank of the matrix A = \(\left[\begin{array}{lll}
1 & 2 & 1&2 \\
1 & 3 & 2 & 2 \\
2 & 4 & 3 & 4 \\
3 & 7 & 4 & 6
\end{array}\right]\) (again the same matrix) by converting it into normal form.
Solution:
Apply R₂ → R₂  R₁, R₃ → R₃  2R₁, and R₄ → R₄  3R₁ we get:
\(\left[\begin{array}{lll}
1 & 2 & 1&2 \\
0 & 1 & 1 & 0 \\
0 & 0 & 1 & 0 \\
0 & 1 & 1 & 0
\end{array}\right]\)
Now apply, R₁ → R₁  2R₂ and R₄ → R₄  R₂,
\(\left[\begin{array}{lll}
1 & 0 & 1&2 \\
0 & 1 & 1 & 0 \\
0 & 0 & 1 & 0 \\
0 & 0 & 0 & 0
\end{array}\right]\)
Apply R₁ → R₁ + R₃ and R₂ → R₂  R₃,
\(\left[\begin{array}{lll}
1 & 0 & 0 &2 \\
0 & 1 & 0 & 0 \\
0 & 0 & 1 & 0 \\
0 & 0 & 0 & 0
\end{array}\right]\)
Now apply C₄ → C₄  2C₁,
\(\left[\begin{array}{lll}
1 & 0 & 0 &0 \\
0 & 1 & 0 & 0 \\
0 & 0 & 1 & 0 \\
0 & 0 & 0 & 0
\end{array}\right]\)
This is same as \(\left[\begin{array}{ll}
I₃ & 0 \\ \\
0 & 0
\end{array}\right]\).
Therefore, the rank of A is, ρ (A) = 3.
Properties of Rank of a Matrix
 If A is a nonsingular matrix of order n, then its rank is n. i.e., ρ (A) = n.
 If A is in Echelon form, then the rank of A = the number of nonzero rows of A.
 If A is in normal form, then the rank of A = the order of the identity matrix in it.
 If A is a singular matrix of order n, then ρ (A) < n.
 If A is a rectangular matrix of order m x n, then ρ (A) ≤ minimum {m, n}.
 The rank of an identity matrix of order n is n itself.
 The rank of a zero matrix is 0.
☛ Related Topics:
Rank of a Matrix Examples

Example 1: Is the rank of the matrix A = \(\left[\begin{array}{lll}
1 & 1 & 1 \\
2 & 3 & 4 \\
2 & 2 & 3
\end{array}\right]\) equal to 3? Justify your answer using determinants.Solution:
The determinant of the given matrix is,
det(A) = 1 (9 + 8)  1 (6  8)  1 (4 + 6)
= 1(1)  1 (2)  1(2)
= 1
≠ 0Therefore, the rank of the matrix A is 3.
Answer: Yes because the determinant of the matrix is NOT 0.

Example 2: Find the rank of matrix A mentioned in Example 1 by converting it into Echelon form.
Solution:
The given matrix is:
\(\left[\begin{array}{lll}
1 & 1 & 1 \\
2 & 3 & 4 \\
2 & 2 & 3
\end{array}\right]\)Apply R₂ → R₂  2R₁ and R₃ → R₃  2R₁, we get:
\(\left[\begin{array}{lll}
1 & 1 & 1 \\
0 & 5 & 6 \\
0 & 4 & 5
\end{array}\right]\)Now, we apply R₃ → 5R₃  4R₂, we get:
\(\left[\begin{array}{lll}
1 & 1 & 1 \\
0 & 5 & 6 \\
0 & 0 & 6
\end{array}\right]\)Now it is in upper triangular form (Echelon form) and there are 3 nonzero rows present in it. Thus, ρ (A) = 3.
Answer: ρ (A) = 3.

Example 3: Find the rank of the 4x4 matrix \(\left[\begin{array}{lll}
0 & 1 & 3 &1 \\
1 & 0 & 1 & 1 \\
3 & 1 & 0 & 2 \\
1 & 1 & 2 & 0
\end{array}\right]\) by converting into normal form.Solution:
Interchanging the first and second columns:
\(\left[\begin{array}{lll}
1 & 0 & 3 &1 \\
0 & 1 & 1 & 1 \\
1 & 3 & 0 & 2 \\
1 & 1 & 2 & 0
\end{array}\right]\)Now, apply R₃ → R₃  R₁ and R₄ → R₄  R₁, we get:
\(\left[\begin{array}{lll}
1 & 0 & 3 &1 \\
0 & 1 & 1 & 1 \\
0 & 3 & 3 & 3 \\
0 & 1 & 1 & 1
\end{array}\right]\)Divide R₃ by 3:
\(\left[\begin{array}{lll}
1 & 0 & 3 &1 \\
0 & 1 & 1 & 1 \\
0 & 1 & 1 & 1 \\
0 & 1 & 1 & 1
\end{array}\right]\)Now, apply R₃ → R₃  R₂ and R₄ → R₄  R₂, we get:
\(\left[\begin{array}{lll}
1 & 0 & 3 &1 \\
0 & 1 & 1 & 1 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 0
\end{array}\right]\)Apply C₃ → C₃ + 3C₁ and C₄ → C₄ + C₁, we get:
\(\left[\begin{array}{lll}
1 & 0 & 0 & 0\\
0 & 1 & 1 & 1 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 0
\end{array}\right]\)Now, apply C₃ → C₃  C₂ and C₄ → C₄  C₂, we get:
\(\left[\begin{array}{lll}
1 & 0 & 0 & 0\\
0 & 1 & 0 & 0 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 0
\end{array}\right]\)This is same as \(\left[\begin{array}{ll}
I₂ & 0 \\ \\
0 & 0
\end{array}\right]\).Thus, ρ (A) = 2.
Answer: ρ (A) = 2.
FAQs on Rank of a Matrix
What is Rank of a Matrix?
The rank of a matrix is the number of linearly independent rows or columns in it. The rank of a matrix A is denoted by ρ (A) which is read as "rho of A". For example, the rank of a zero matrix is 0 as there are no linearly independent rows in it.
How Do You Find the Rank of a Matrix?
To find the rank of a matrix, we can use one of the following methods:
 Find the highest ordered nonzero minor and its order would give the rank.
 Convert the matrix into echelon form using the row/column operations. Then the number of nonzero rows in it would give the rank of the matrix.
 Convert the matrix into the normal form \(\left[\begin{array}{ll}
Iᵣ & 0 \\ \\
0 & 0
\end{array}\right]\), where Iᵣ is the identity matrix of order 'r'. Then rank of the matrix = r.
What is the Rank of a Matrix of Order 3x3?
The rank of a matrix of order 3x3 is 3 if its determinant is NOT 0. If its determinant is 0, then convert it into Echelon form by using row/column transformations, then the number of nonzero rows/columns would give the rank.
What is the Rank of a Matrix of Order 2x2?
If the determinant of a 2x2 matrix is NOT 0, then its rank is 2. If its determinant is 0, then its rank is either 1 or 0. The exact rank can be found by converting it into echelon form or normal form.
How to Find the Rank of a Matrix Using Determinant?
To find the rank of a matrix of order n, first, compute its determinant (in the case of a square matrix). If it is NOT 0, then its rank = n. If it is 0, then see whether there is any nonzero minor of order n  1. If such minor exists, then the rank of the matrix = n  1. If all the minors of order n  1 are zeros, then we should repeat the process for minors of order n  2, and so on until we are able to find the rank.
What is the Shortcut to Find the Rank of a Matrix?
If the determinant of a matrix is not zero, then the rank of the matrix is equal to the order of the matrix. This can be used as a shortcut. But this shortcut does not work when the determinant is 0. In this case, we have to use either minors, Echelon form, or normal form to find the rank like how the processes are explained on this page.
What Does the Rank of a Matrix Tell Us?
The rank of a matrix would give the number of linearly independent rows (or columns). The more the rank of the matrix the more the linearly independent rows and also the more the informative content.
What is the Relation Between the Rank of a Matrix and Eigenvalues?
There is a very close relationship between the rank of a matrix and the eigenvalues. The rank of a matrix is exactly equal to the number of nonzero eigenvalues.
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