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Systems of linear equations and larger matrices in QCE Specialist Mathematics Unit 3

Syllabus dot point

“Use matrices beyond order two, including the determinant and inverse of a three by three matrix, to represent and solve systems of linear equations, and interpret unique, infinite and no-solution cases geometrically”

QCESpecialist MathematicsUnit 3: Mathematical induction, and…8 min read

Quick answer

Write three linear equations as Ax=bA\mathbf{x} = \mathbf{b}. The 3×33\times 3 determinant, expanded along a row with signs +,−,++,-,+, decides invertibility. If det⁡A≠0\det A \neq 0 there is a unique solution x=A−1b\mathbf{x} = A^{-1}\mathbf{b} and the three planes meet at one point. If det⁡A=0\det A = 0, the system has either no solution (inconsistent, no common point) or infinitely many (consistent, the planes share a line), determined by testing consistency.

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  1. What this dot point is asking
  2. The answer
  3. Exam-style questions

What this dot point is asking

QCAA wants you to handle matrices larger than 2×22\times 2, especially to represent a system of three linear equations in three unknowns as Ax=bA\mathbf{x} = \mathbf{b}, solve it using the inverse x=A−1b\mathbf{x} = A^{-1}\mathbf{b}, and interpret what happens when the determinant is zero. The geometric reading, three planes meeting in a point, in a line or not at all, ties the algebra to the vectors topic.

The answer

Matrix form of a system

A system such as

a1x+b1y+c1z=d1a2x+b2y+c2z=d2a3x+b3y+c3z=d3 \begin{aligned} a_1 x + b_1 y + c_1 z &= d_1\\ a_2 x + b_2 y + c_2 z &= d_2\\ a_3 x + b_3 y + c_3 z &= d_3 \end{aligned}

is written compactly as Ax=bA\mathbf{x} = \mathbf{b}, where AA is the 3×33\times 3 matrix of coefficients, x=(x,y,z)T\mathbf{x} = (x, y, z)^{\mathsf T} and b=(d1,d2,d3)T\mathbf{b} = (d_1, d_2, d_3)^{\mathsf T}.

Determinant of a three by three matrix

Expanding along the first row,

det⁡A=a1∣b2c2b3c3∣−b1∣a2c2a3c3∣+c1∣a2b2a3b3∣.\det A = a_1\begin{vmatrix} b_2 & c_2\\ b_3 & c_3\end{vmatrix} - b_1\begin{vmatrix} a_2 & c_2\\ a_3 & c_3\end{vmatrix} + c_1\begin{vmatrix} a_2 & b_2\\ a_3 & b_3\end{vmatrix}.

The alternating signs (+,−,++, -, +) are essential. The determinant decides invertibility: AA has an inverse if and only if det⁡A≠0\det A \neq 0.

Inverse and solving

When det⁡A≠0\det A \neq 0 the system has a unique solution

x=A−1b.\mathbf{x} = A^{-1}\mathbf{b}.

In practice the inverse of a 3×33\times 3 matrix is found from the adjugate divided by the determinant, or computed with technology, which QCAA permits in the relevant assessment. The point is to recognise the structure and read off the unique solution.

Geometric interpretation

Each equation ax+by+cz=dax + by + cz = d is a plane. Solving the system locates the common points of three planes.

  • Unique solution (det⁡A≠0\det A \neq 0): the three planes meet at a single point.
  • No solution (det⁡A=0\det A = 0, system inconsistent): the planes have no common point, for example two are parallel, or they form a triangular prism arrangement.
  • Infinitely many solutions (det⁡A=0\det A = 0, system consistent): the planes share a common line, or all coincide, giving a one-parameter family of solutions.

Why the determinant matters

A zero determinant signals that the rows (or the normal vectors of the planes) are linearly dependent, so the inverse method fails. You then test consistency directly by elimination to decide between no solution and infinitely many.

Solving by elimination (row reduction)

When the inverse is not used, Gaussian elimination is the systematic alternative. Use one equation to eliminate a variable from the others, then repeat, reducing the system to an upper-triangular form that can be back-substituted. If elimination produces a contradictory row such as 0=50 = 5, the system is inconsistent and has no solution. If it produces an all-zero row such as 0=00 = 0, one equation was dependent on the others, leaving a free variable and infinitely many solutions. This procedure works whether or not the determinant is zero, and it is the tool that distinguishes the two degenerate cases.

Parametrising an infinite solution set

When there are infinitely many solutions, express the answer with a parameter. Solve for two variables in terms of the third, set the free variable equal to tt, and write the solution as x=x0+td\mathbf{x} = \mathbf{x}_0 + t\mathbf{d}. Geometrically this is exactly the line of intersection of the three planes: x0\mathbf{x}_0 is one point on the line and d\mathbf{d} is its direction. Recognising the parametric solution as a line ties this dot point back to vector equations of lines, and QCAA rewards stating the geometric interpretation alongside the algebra.

Reading the geometry of three planes

It helps to picture the configurations. Three planes meeting at a single point give a unique solution. Three planes sharing a common line give a one-parameter family. Three planes with no common point arise either when two are parallel and distinct, or when each pair meets in a line but the three lines are parallel (a triangular-prism arrangement). Coincident planes (all the same plane) give a two-parameter family. Matching the algebraic outcome to one of these pictures is the kind of justification an extended-response item asks for.

Solve the system x+y+z=6x + y + z = 6,   2x−y+z=3\; 2x - y + z = 3,   x+2y−z=2\; x + 2y - z = 2.

Step 1: Form the coefficient matrix and compute the determinant

Arrange the coefficients of xx, yy, zz into the matrix AA:

A=(1112−1112−1)A = \begin{pmatrix} 1 & 1 & 1\\ 2 & -1 & 1\\ 1 & 2 & -1\end{pmatrix}

Expand along the first row with alternating signs (+,−,+)(+, -, +):

det⁡A=1[(−1)(−1)−(1)(2)]−1[(2)(−1)−(1)(1)]+1[(2)(2)−(−1)(1)]\det A = 1\big[(-1)(-1) - (1)(2)\big] - 1\big[(2)(-1) - (1)(1)\big] + 1\big[(2)(2) - (-1)(1)\big]

det⁡A=1(1−2)−1(−2−1)+1(4+1)=−1+3+5=7\det A = 1(1 - 2) - 1(-2 - 1) + 1(4 + 1) = -1 + 3 + 5 = 7

Because det⁡A=7≠0\det A = 7 \neq 0, the matrix is invertible and the system has a unique solution.

Step 2: Eliminate zz to get two equations in two unknowns

Subtract equation 1 from equation 2 to cancel zz:

(2x−y+z)−(x+y+z)=3−6  ⟹  x−2y=−3(2x - y + z) - (x + y + z) = 3 - 6 \implies x - 2y = -3

Add equation 1 and equation 3 to cancel zz:

(x+y+z)+(x+2y−z)=6+2  ⟹  2x+3y=8(x + y + z) + (x + 2y - z) = 6 + 2 \implies 2x + 3y = 8

Step 3: Solve the two-variable system for yy, then xx

From x−2y=−3x - 2y = -3, express x=2y−3x = 2y - 3. Substitute into 2x+3y=82x + 3y = 8:

2(2y−3)+3y=8  ⟹  7y=14  ⟹  y=22(2y - 3) + 3y = 8 \implies 7y = 14 \implies y = 2

Then x=2(2)−3=1x = 2(2) - 3 = 1.

Step 4: Back-substitute to find zz, then verify

From equation 1: z=6−x−y=6−1−2=3z = 6 - x - y = 6 - 1 - 2 = 3.

Check in equation 2: 2(1)−2+3=32(1) - 2 + 3 = 3. Correct.

Final answer: (x,y,z)=(1,2,3)(x, y, z) = (1, 2, 3), the single point at which the three planes intersect.

Common trap

The most common error is dropping the alternating sign in the cofactor expansion, especially the leading minus on the middle term, which corrupts the determinant. A second mistake is concluding "no solution" the instant the determinant is zero; a zero determinant means the inverse method fails, but the system may still have infinitely many solutions. Test consistency by elimination before deciding between no solution and infinitely many.

Exam-style questions

Questions in the style of QCAA exam questions on this dot point, each with a worked answer. They are written by ExamExplained unless tagged "Past paper"; the year shows the paper a question is modelled on.

Practice4 marks
Paper 2 (complex familiar). A system is given by x−2y−2z=−6x - 2y - 2z = -6, −3x−y+z=2-3x - y + z = 2 and 2x+3y−5z=102x + 3y - 5z = 10. (a) Express the system as a matrix equation Ax=bA\mathbf{x} = \mathbf{b}. (b) Express x\mathbf{x} in terms of AA and b\mathbf{b}. (c) Determine the solution. (d) Verify using one of the equations.
Show worked answer →

(a) [1 mark] A=(1−2−2−3−1123−5)A = \begin{pmatrix} 1 & -2 & -2 \\ -3 & -1 & 1 \\ 2 & 3 & -5 \end{pmatrix}, x=(x,y,z)T\mathbf{x} = (x, y, z)^{\mathsf T}, b=(−6,2,10)T\mathbf{b} = (-6, 2, 10)^{\mathsf T}, so Ax=bA\mathbf{x} = \mathbf{b}.

(b) [1 mark] Since det⁡A≠0\det A \neq 0, pre-multiply by A−1A^{-1}: x=A−1b\mathbf{x} = A^{-1}\mathbf{b}.

(c) [1 mark] Evaluating A−1bA^{-1}\mathbf{b} (by calculator on this technology-active paper) gives x=(−2,3,−1)T\mathbf{x} = (-2, 3, -1)^{\mathsf T}, that is x=−2x = -2, y=3y = 3, z=−1z = -1.

(d) [1 mark] In equation one: (−2)−2(3)−2(−1)=−2−6+2=−6(-2) - 2(3) - 2(-1) = -2 - 6 + 2 = -6, matching the right-hand side, so the solution is verified.

Practice4 marks
Paper 1 (technique). The matrix A=(21−11−12301)A = \begin{pmatrix} 2 & 1 & -1 \\ 1 & -1 & 2 \\ 3 & 0 & 1 \end{pmatrix} is the coefficient matrix of a system Ax=bA\mathbf{x} = \mathbf{b}. (a) Determine det⁡A\det A by cofactor expansion along the first row. (b) State, with reason, whether the system has a unique solution for every b\mathbf{b}.
Show worked answer →

(a) det⁡A=2[(−1)(1)−(2)(0)]−1[(1)(1)−(2)(3)]+(−1)[(1)(0)−(−1)(3)]\det A = 2\big[(-1)(1) - (2)(0)\big] - 1\big[(1)(1) - (2)(3)\big] + (-1)\big[(1)(0) - (-1)(3)\big] =2(−1)−1(1−6)−1(0+3)=−2+5−3=0.= 2(-1) - 1(1 - 6) - 1(0 + 3) = -2 + 5 - 3 = 0.

(b) Since det⁡A=0\det A = 0, AA is not invertible, so the system does not have a unique solution for every b\mathbf{b}; depending on b\mathbf{b} it has either no solution or infinitely many.

Markers reward the cofactor expansion with the correct alternating signs and the conclusion that a zero determinant rules out a unique solution.

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