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How to Solve a 3×3 Matrix

“Solve a 3×3 matrix” can mean a few different tasks: finding the determinant, checking whether the matrix is invertible, computing an inverse, or solving a 3-variable linear system. The good news is that one tool—row reduction—solves most of these reliably. Determinants help you decide what to expect before you do a lot of work.

📊 Linear Algebra⏱️ ~28 min read🔴 Advanced

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Step 0: What Does “Solve” Mean Here?

  • Determinant: a number det(A) that tells you if A is invertible (and encodes volume scaling).
  • Inverse: A^-1 such that A·A^-1 = I (only exists if det(A) ≠ 0).
  • System: solve Ax = b for a 3-variable vector x (unique / infinite / none).

If your problem statement includes “solve the system” or gives three equations, you want row reduction. If it asks “is the matrix invertible?” compute the determinant or row-reduce A to see if it pivots in every column.

Determinant Intuition (Why You Care)

For a 3×3 matrix A, the determinant det(A) tells you whether the matrix is invertible. If det(A) ≠ 0, the matrix is invertible and a system Ax=b has a unique solution for every b. If det(A) = 0, the matrix is singular and you may have no solution or infinitely many solutions depending on b.

There is also a geometry meaning: |det(A)| is the volume scale factor of a 3D transformation, and the sign indicates whether orientation flips. You don’t need that geometry meaning to solve homework, but it helps explain why det(A)=0 means the matrix “flattens” space and loses information.

How to Compute det(A) (Cofactor Expansion)

A common method for 3×3 determinants is expanding along the first row. You break the determinant into three 2×2 determinants. This is algebra-heavy, so go slow and keep signs organized.

Example: Compute det(A) for

A = [[1, 2, 0], [3, 1, 4], [2, 0, 1]]

Expand along the first row (sign pattern + − +):

det(A) = 1·det([[1, 4], [0, 1]]) − 2·det([[3, 4], [2, 1]]) + 0·(...)
= 1·(1·1 − 4·0) − 2·(3·1 − 4·2)
= 1·(1) − 2·(3 − 8)
= 1 − 2·(−5) = 11

Since det(A) = 11 ≠ 0, A is invertible and any system Ax=b has a unique solution.

Row Reduction (The Most Reliable “Solve” Tool)

If you are solving a 3×3 system, row-reduce the augmented matrix [A | b]. Your goal is to reach reduced row echelon form (RREF) so you can read off x, y, z.

Allowed row operations:

  • Swap two rows.
  • Multiply a row by a nonzero constant.
  • Add a multiple of one row to another row.

Worked Example: Solve a 3×3 System

Problem: Solve the system

x + y + z = 6
2x + y + 3z = 13
x + 3y + 2z = 11

Write it as an augmented matrix [A | b] and row-reduce:

[1 1 1 | 6]
[2 1 3 | 13]
[1 3 2 | 11]
R2 → R2 − 2R1:
[1 1 1 | 6]
[0 −1 1 | 1]
[1 3 2 | 11]
R3 → R3 − R1:
[1 1 1 | 6]
[0 −1 1 | 1]
[0 2 1 | 5]

Now eliminate y from the third row using row 2:

R3 → R3 + 2R2:
[1 1 1 | 6]
[0 −1 1 | 1]
[0 0 3 | 7]

From the last row: 3z = 7 so z = 7/3. Then row 2 says −y + z = 1, so y = z − 1 = 7/3 − 1 = 4/3. Finally row 1 gives x + y + z = 6, so x = 6 − 4/3 − 7/3 = 6 − 11/3 = 7/3.

Solution: x = 7/3, y = 4/3, z = 7/3.

How to Check Your Answer Quickly

For a system Ax=b, checking is straightforward: compute A·x and confirm it equals b. If you’re solving with three equations, substitute your values back into the original equations and confirm each one is true.

  • Check one equation? That’s a partial check. Check all three.
  • If you got fractions, keep them exact during the check instead of rounding.
  • If a determinant is nonzero, you should not end with free variables.

Common Mistakes

Sign errors in cofactors

The cofactor sign pattern is + − + on the first row. A single sign mistake can flip your determinant.

Messy row operations

Write each row operation explicitly. “Mental row reduction” causes lost terms and wrong pivots.

Rounding too early

If you get fractions, keep them until the final answer. Rounding mid-way can drift enough to fail checks.

Confusing determinant with solution

det(A) tells you about invertibility, not the values of x, y, z. You still need row reduction to solve.

If you want additional practice and intuition for determinants and row reduction, the lessons in MIT OpenCourseWare 18.06 Linear Algebra are a gold-standard reference.

Practice Problems

  1. Compute det(A) for A = [[2, 1, 0], [0, 3, 4], [1, 0, 5]].
  2. Solve the system: x + 2y + z = 7, 2x + y + 3z = 13, x + y + 2z = 10.
  3. Row-reduce the matrix [[1, 2, 3], [2, 4, 7], [1, 1, 1]] and determine if it is invertible.
  4. Explain what det(A) = 0 means in terms of solutions to Ax=b.

A Final Tip: Prefer Row Reduction Under Time Pressure

If you’re choosing a method during a quiz, row reduction is usually the safest because it works whether det(A) is zero or nonzero, and it directly tells you whether a system has one solution, infinitely many, or none. Determinants are still useful as a quick invertibility test, but row reduction is the method that consistently gets you to a verified answer.

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How to Solve a 3x3 Matrix | Determinant, Inverse, Row Reduction (Step-by-Step)