Rank of Matrix: The **rank** of a matrix is defined as:

1 The maximum number of linearly independent *column* vectors in the matrix

2 The maximum number of linearly independent *row* vectors in the matrix.

For any matrix with dimensions of m*n

1 If m is less than n then maximum rank of a matrix is n

2 If m is greater than n then maximum rank of a matrix is m

The rank of a matrix would be zero only if the matrix had no elements. If a matrix had even one element, its minimum rank would be one.

**How to determine Rank of a Matrix**: In this section, we describe a method for finding the rank of any matrix.

The maximum number of linearly independent vectors in a matrix is equal to the number of non-zero rows in itsrow echelon matrix. Therefore, to find the rank of a matrix, we simply transform the matrix to its row echelon form and count the number of non-zero rows.

Consider matrix **A** and its row echelon matrix, **Aref**.

Because the row echelon form **A _{ref}** has two non-zero rows, we know that matrix

**A**has two independent row vectors; and we know that the rank of matrix

**A**is 2.

You can verify that this is correct. Row 1 and Row 2 of matrix **A** are linearly independent. However, Row 3 is a linear combination of Rows 1 and 2. Specifically, Row 3 = 3*( Row 1 ) + 2*( Row 2). Therefore, matrix **A** has only two independent row vectors.