**Singular matrix** is a square matrix whose determinant is zero. It is also known as **non invertible matrix** or **degenerate matrix**. A square matrix whose determinant is not zero is known as **non singular matrix**. It is also known as **invertible matrix** or **non** **degenerate matrix**.

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A square matrix P is said to be singular matrix if |P| = 0. A square matrix Q is said to be non singular matrix if |Q| ≠ 0.

## Singular matrix examples

The example of a singular matrix of order 3 (or matrix size is 3 x 3) is given below.

The example of a singular matrix of order 2 (or matrix size is 2 x 2) is given below.

## Non Singular matrix examples

The example of non singular matrix of order 3 (or matrix size is 3 x 3) is given below.

The example of non singular matrix of order 2 (or matrix size is 2 x 2) is given below.

## Singular matrix properties

1. The determinant of a singular matrix (P) is zero i.e. |P| = 0.

2. The inverse of a singular matrix does not exist. Hence it is also known as non-invertible matrix.

3. This matrix is always a square matrix because determinant is always calculated for a square matrix.

4. There is no multiplicative inverse exist for this matrix.

## Non Singular matrix properties

1. The determinant of a non singular matrix (Q) is not zero i.e. |Q| ≠ 0.

2. The inverse of a non singular matrix does exist. Hence it is also known as invertible matrix.

3. Such matrix is always a square matrix because determinant is always calculated for a square matrix.