Matrix Rank Calculator

Calculate the rank of a matrix using Gaussian elimination with step-by-step solutions

Matrix Input

Matrix Elements

Enter matrix elements. Use decimal numbers (e.g., 0.5, -2.3)

Quick Examples

Matrix Rank Results

2
Matrix Rank
1
Nullity
3
Max Possible Rank
NO
Full Rank

Matrix Properties

  • Full Row Rank:No
  • Full Column Rank:No
  • Invertible:No

Rank Formula

Rank: Number of linearly independent rows/columns

Nullity: n - rank(A) = 3 - 2 = 1

Rank-Nullity Theorem: rank + nullity = 3

Step-by-Step Solution

1. Starting with 3×3 matrix
2. Row 1 ↔ Row 3
3. Using pivot 7.000 at position (1, 1)
4. R2 → R2 - 0.571 × R1
5. R3 → R3 - 0.143 × R1
6. Row 2 ↔ Row 3
7. Using pivot 0.857 at position (2, 2)
8. R3 → R3 - 0.500 × R2
9. Column 3: No non-zero pivot found
10. Final rank: 2 (number of non-zero rows)

Row Echelon Form

7.000
8.000
9.000
0
0.857
1.714
0
0
0

This is the row echelon form obtained through Gaussian elimination

Matrix Rank Guide

1

Set Dimensions

Choose matrix size (up to 5×5)

2

Enter Elements

Fill in matrix values

3

Get Results

Rank calculated automatically

Key Concepts

Rank: Number of linearly independent rows or columns

Full Rank: rank(A) = min(m,n)

Nullity: n - rank(A)

Gaussian Elimination: Method to find rank

Understanding Matrix Rank

What is Matrix Rank?

The rank of a matrix is the maximum number of linearly independent rows (or equivalently, columns) in the matrix. It represents the dimension of the vector space spanned by the matrix's rows or columns.

How to Calculate Rank

  • Use Gaussian elimination to transform matrix to row echelon form
  • Count the number of non-zero rows
  • This count equals the matrix rank

Important Properties

  • Rank-Nullity Theorem: rank(A) + nullity(A) = n
  • Maximum Rank: rank(A) ≤ min(m, n)
  • Full Rank: rank(A) = min(m, n)
  • Invertible: Square matrix A is invertible ↔ rank(A) = n

Applications

  • Solving systems of linear equations
  • Determining matrix invertibility
  • Linear independence verification