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Mastering Elementary Operations & Rank of a Matrix

Complete guide to Elementary Row Operations and Matrix Rank with step-by-step methods for JEE Main & Advanced preparation.

3
Elementary Operations
5+
Rank Methods
12
Solved Examples
95%
JEE Relevance

Why Elementary Operations & Rank Matter in JEE

Elementary Operations and Matrix Rank are fundamental concepts that appear in 15-20% of JEE Linear Algebra questions. Mastering these will help you solve:

  • System of Linear Equations - Consistency and solutions
  • Matrix Inversion - Finding inverse using elementary operations
  • Determinant Calculations - Simplified computation
  • Vector Spaces - Basis and dimension concepts
  • Eigenvalue Problems - Characteristic equations
Fundamental Concept Easy

Three Types of Elementary Row Operations

Type 1: Row Switching ($R_i \leftrightarrow R_j$)

Interchange two rows of the matrix. This operation doesn't change the determinant's absolute value (only sign).

Type 2: Row Multiplication ($kR_i \rightarrow R_i$)

Multiply a row by a non-zero scalar $k$. This multiplies the determinant by $k$.

Type 3: Row Addition ($R_i + kR_j \rightarrow R_i$)

Add a multiple of one row to another row. This doesn't change the determinant.

Example:

Apply $R_2 \leftrightarrow R_3$ to matrix $A = \begin{bmatrix} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end{bmatrix}$

Result: $\begin{bmatrix} 1 & 2 & 3 \\ 7 & 8 & 9 \\ 4 & 5 & 6 \end{bmatrix}$

JEE Main 2023 Medium

Finding Rank Using Elementary Operations

Reduce the matrix to Row Echelon Form (REF) and count non-zero rows.

Step-by-Step Example:

Given Matrix: $A = \begin{bmatrix} 1 & 2 & 3 \\ 2 & 4 & 6 \\ 3 & 6 & 9 \end{bmatrix}$

Step 1: $R_2 \rightarrow R_2 - 2R_1$

$\begin{bmatrix} 1 & 2 & 3 \\ 0 & 0 & 0 \\ 3 & 6 & 9 \end{bmatrix}$

Step 2: $R_3 \rightarrow R_3 - 3R_1$

$\begin{bmatrix} 1 & 2 & 3 \\ 0 & 0 & 0 \\ 0 & 0 & 0 \end{bmatrix}$

Step 3: Matrix is in REF with 1 non-zero row

Conclusion: Rank(A) = 1

JEE Advanced 2022 Hard

Rank and System of Equations

For system $AX = B$, where $A$ is coefficient matrix and $[A|B]$ is augmented matrix:

Consistency Conditions:

  • Consistent: Rank(A) = Rank([A|B])
  • Unique Solution: Rank(A) = Rank([A|B]) = Number of variables
  • Infinite Solutions: Rank(A) = Rank([A|B]) < Number of variables
  • Inconsistent: Rank(A) ≠ Rank([A|B])

Problem:

Determine consistency of: $$\begin{cases} x + 2y + 3z = 1 \\ 2x + 4y + 6z = 2 \\ 3x + 6y + 9z = 4 \end{cases}$$

Step 1: Coefficient matrix $A = \begin{bmatrix} 1 & 2 & 3 \\ 2 & 4 & 6 \\ 3 & 6 & 9 \end{bmatrix}$

Step 2: Augmented matrix $[A|B] = \begin{bmatrix} 1 & 2 & 3 & | & 1 \\ 2 & 4 & 6 & | & 2 \\ 3 & 6 & 9 & | & 4 \end{bmatrix}$

Step 3: Rank(A) = 1 (from previous example)

Step 4: Apply operations to $[A|B]$:

• $R_2 \rightarrow R_2 - 2R_1$: $\begin{bmatrix} 1 & 2 & 3 & | & 1 \\ 0 & 0 & 0 & | & 0 \\ 3 & 6 & 9 & | & 4 \end{bmatrix}$

• $R_3 \rightarrow R_3 - 3R_1$: $\begin{bmatrix} 1 & 2 & 3 & | & 1 \\ 0 & 0 & 0 & | & 0 \\ 0 & 0 & 0 & | & 1 \end{bmatrix}$

Step 5: Rank([A|B]) = 2 ≠ Rank(A) = 1

Conclusion: System is inconsistent

🚀 Key Properties & Shortcuts

Rank Properties:

  • Rank ≤ min(rows, columns)
  • Rank(A) = Rank(AT)
  • Rank(AB) ≤ min(Rank(A), Rank(B))
  • For square matrix: Rank = n ⇔ det(A) ≠ 0

Elementary Operations Tips:

  • Always work systematically left to right
  • Create zeros below pivots first
  • Use fractions carefully to avoid errors
  • Check your work by verifying operations

Advanced Concepts Available in Full Version

Includes: Elementary Column Operations, Finding Inverse using E.O., Rank-Nullity Theorem, Special Matrices, and 8+ Practice Problems

📝 Quick Self-Test

Try these JEE-level problems to test your understanding:

1. Find rank of $\begin{bmatrix} 1 & 2 & 1 \\ 2 & 4 & 2 \\ 1 & 2 & 3 \end{bmatrix}$

2. Using elementary operations, find inverse of $\begin{bmatrix} 1 & 2 \\ 3 & 4 \end{bmatrix}$

3. For what value of k does the system have infinite solutions?
$\begin{cases} x + 2y = 3 \\ 2x + ky = 6 \end{cases}$

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