Find the rank of a 3×3 matrix using row echelon form

medium JEE-MAIN JEE Main 2022 3 min read

Question

Find the rank of the matrix:

A=(123235358)A = \begin{pmatrix} 1 & 2 & 3 \\ 2 & 3 & 5 \\ 3 & 5 & 8 \end{pmatrix}

(JEE Main 2022, similar pattern)


Solution — Step by Step

Start with the matrix and perform R2R22R1R_2 \to R_2 - 2R_1 and R3R33R1R_3 \to R_3 - 3R_1:

(123011011)\begin{pmatrix} 1 & 2 & 3 \\ 0 & -1 & -1 \\ 0 & -1 & -1 \end{pmatrix}

Apply R3R3R2R_3 \to R_3 - R_2:

(123011000)\begin{pmatrix} 1 & 2 & 3 \\ 0 & -1 & -1 \\ 0 & 0 & 0 \end{pmatrix}

This is the row echelon form.

The row echelon form has 2 non-zero rows.

Rank(A)=2\boxed{\text{Rank}(A) = 2}

Why This Works

The rank of a matrix equals the number of non-zero rows in its row echelon form. Row operations don’t change the rank because they don’t change the row space — they just rewrite the same set of linear combinations in a simpler form.

The third row becoming all zeros means R3R_3 was a linear combination of R1R_1 and R2R_2. Indeed, (3,5,8)=(1,2,3)+(2,3,5)(3, 5, 8) = (1, 2, 3) + (2, 3, 5). So only 2 of the 3 rows are linearly independent.

An equivalent check: if A=0|A| = 0 (which it is here, since a row of zeros gives determinant 0), then the rank is strictly less than 3. We then check if any 2×22 \times 2 minor is non-zero to confirm rank = 2.


Alternative Method — Determinant approach

Compute A|A|: expand and get A=0|A| = 0 (you can verify: the third row is the sum of the first two).

Since A=0|A| = 0, rank <3< 3. Now check 2×22 \times 2 minors. Take the top-left 2×22 \times 2: 1223=34=10\begin{vmatrix} 1 & 2 \\ 2 & 3 \end{vmatrix} = 3 - 4 = -1 \neq 0.

Since a non-zero 2×22 \times 2 minor exists, rank 2\geq 2. Combined: rank = 2.

For JEE MCQs, the determinant method is faster. Check A=0|A| = 0 (rank < 3), then check one 2×22 \times 2 minor (if non-zero, rank = 2). The row echelon method is more systematic for larger matrices or when you need to find the actual independent rows.


Common Mistake

Students sometimes conclude that rank = 0 when they see a row of zeros, confusing “one zero row” with “rank is zero.” Rank equals the number of non-zero rows, not zero rows. A 3×33 \times 3 matrix with one zero row in echelon form has rank 2, not 0 or 1. Rank = 0 only for the zero matrix (all entries zero).

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