Matrix Rank and Nullity Calculator

Find matrix rank, nullity, pivots, free variables, echelon forms, and null-space bases with clear steps, exact fractions, exports, and reliable verification for every matrix.

Enter Matrix Values

Choose the matrix size and number mode. Enter every value in the generated grid. Then calculate the complete rank analysis.

Choose between one and twelve rows.
Nullity uses this column count.
Exact mode preserves rational values.
Used when decimal mode is selected.
Small decimal values can count as zero.
Separate values using spaces, commas, tabs, or new lines.

Matrix Grid

Reset

Formula Used

rank(A) + nullity(A) = number of columns in A

Rank counts pivot columns after row reduction. Nullity counts independent free-variable directions. Their sum always equals the column count.

How to Use

Select the required rows and columns. Enter integers, decimals, or fraction values. Press calculate to inspect every result.

  1. Choose dimensions between one and twelve.
  2. Select exact or decimal output mode.
  3. Enter values manually or paste matrix data.
  4. Enable steps for detailed elimination history.
  5. Review pivots, bases, properties, and verification.
  6. Export the finished analysis when needed.

Example Data

These examples show common rank patterns. Nullity always uses the number of columns. Dependent columns increase the free-variable count.

Matrix type Rows Columns Rank Nullity
Identity matrix3330
Zero matrix3404
Dependent columns3321
Full row rank2422
Full column rank4220

Key Concepts

Matrix Rank

Rank measures independent rows or columns. It equals the number of pivots. Larger rank means more independent information.

Matrix Nullity

Nullity measures solutions to Ax equals zero. It equals the free-variable count. Each free variable creates one basis direction.

Pivot and Free Variables

Pivot columns contain leading entries in RREF. Other columns represent free variables. Those variables generate the null-space basis.

Common Mistakes

Do not calculate nullity from row count. Avoid rounding too early during elimination. Check fraction signs and zero tolerance carefully.

Applications

Rank detects redundant equations and features. Nullity describes unconstrained solution directions. Both support modelling, graphics, and data analysis.

Frequently Asked Questions

What is matrix rank?

Matrix rank counts independent rows or columns. It equals the pivot count after reduction. Rank cannot exceed either matrix dimension.

What is matrix nullity?

Nullity is the null-space dimension. It equals the number of free variables. Nullity cannot exceed the column count.

Why does nullity use columns?

Each column corresponds to one unknown. Pivot columns determine leading variables. Remaining columns create free variables and nullity.

Can rectangular matrices have nullity?

Yes, rectangular matrices have nullity. The same rank-nullity theorem still applies. Subtract rank from the column count.

What does full column rank mean?

Every column is linearly independent. Rank then equals the column count. The nullity must therefore equal zero.

What does full row rank mean?

Every row is linearly independent. Rank then equals the row count. Extra columns can still create nullity.

Does transpose change matrix rank?

No, transposition preserves matrix rank. Row rank always equals column rank. The calculator verifies this property automatically.

How does tolerance affect results?

Tolerance treats tiny decimals as zero. It helps manage measured or approximate data. Exact mode ignores tolerance for rational zeroes.

When is a square matrix invertible?

A square matrix is invertible at full rank. Its determinant is then nonzero. Its nullity also equals zero.

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Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.