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Chapter 4 · Determinants

Exercise 4.5 · Q10: Solve 5x+2y=35x+2y=3⁠, 3x+2y=53x+2y=5 by the matrix method

Exercise 4.5Solving systems AX = B · Section 4.6.1
The question

Solve system of linear equations, using matrix method, in Exercises 7 to 14.

10.

5x+2y=33x+2y=5\begin{aligned} 5x + 2y &= 3\\ 3x + 2y &= 5 \end{aligned}
Exam answer

The system is AX=BAX = B⁠, where

A=[5232],X=[xy], B=[35]\begin{aligned} A &= \begin{bmatrix} 5 & 2 \\ 3 & 2 \end{bmatrix}, \\ X &= \begin{bmatrix} x \\ y \end{bmatrix},\ B = \begin{bmatrix} 3 \\ 5 \end{bmatrix} \end{aligned} ∣A∣=∣5232∣=10−6=4|A| = \begin{vmatrix} 5 & 2 \\ 3 & 2 \end{vmatrix} = 10 - 6 = 4

∣A∣=4≠0|A| = 4 \ne 0⁠. So A−1A^{-1} exists and the system has a unique solution, X=A−1BX = A^{-1}B⁠.

adj⁡A=[2−2−35]A−1=1∣A∣adj⁡A=14[2−2−35]\begin{aligned} \operatorname{adj}A &= \begin{bmatrix} 2 & -2 \\ -3 & 5 \end{bmatrix} \\ A^{-1} &= \frac{1}{|A|}\operatorname{adj}A \\ &= \frac{1}{4}\begin{bmatrix} 2 & -2 \\ -3 & 5 \end{bmatrix} \end{aligned} X=A−1B=14[2−2−35][35]=14[6−10−9+25]=14[−416]=[−14]\begin{aligned} X &= A^{-1}B \\ &= \frac{1}{4}\begin{bmatrix} 2 & -2 \\ -3 & 5 \end{bmatrix}\begin{bmatrix} 3 \\ 5 \end{bmatrix} \\ &= \frac{1}{4}\begin{bmatrix} 6 - 10 \\ -9 + 25 \end{bmatrix} \\ &= \frac{1}{4}\begin{bmatrix} -4 \\ 16 \end{bmatrix} = \begin{bmatrix} -1 \\ 4 \end{bmatrix} \end{aligned}

∴ x=−1, y=4\therefore\ x = -1,\ y = 4⁠.

Want the reason behind every step, the basics and the checks?

The one idea this problem is built on

The system is the single matrix equation AX=BAX = B⁠. Because ∣A∣≠0|A| \ne 0⁠, the matrix AA can be undone: multiplying on the left by A−1=1∣A∣adj⁡AA^{-1} = \frac{1}{|A|}\operatorname{adj} A leaves X=A−1BX = A^{-1}B, and that column is the one and only solution.

Given, to find, and the plan
Given
The equations 5x+2y=35x + 2y = 3 and 3x+2y=53x + 2y = 5⁠.
To find
xx and yy⁠, using the matrix method.
Plan
(1) Write AX=BAX = B⁠. (2) Compute ∣A∣|A|⁠. (3) Cofactors and adj⁡A\operatorname{adj} A⁠. (4) A−1A^{-1}⁠, with the check AA−1=IAA^{-1} = I⁠. (5) X=A−1BX = A^{-1}B⁠. (6) Check in both equations.

Basics you need

1A system is a matrix product

Row ii of AA times the column XX is the left side of equation ii⁠, so AX=BAX = B holds exactly when every equation holds. Basics: matrix facts the chapter uses

2The 2×22\times2 determinant

For rows (a,b)(a, b) and (c,d)(c, d)⁠, the determinant is ad−bcad - bc⁠. Basics: where the determinant comes from

3Cofactors and the adjoint

Aij=(−1)i+jMijA_{ij} = (-1)^{i+j}M_{ij}⁠; the adjoint is the transpose of the matrix of cofactors. For 2×22\times2⁠: swap the diagonal entries and change the signs of the other two. Basics: the + − + sign pattern

4The inverse

If ∣A∣≠0|A| \ne 0⁠, then A−1=1∣A∣adj⁡AA^{-1} = \frac{1}{|A|}\operatorname{adj} A⁠, because A(adj⁡A)=∣A∣ IA(\operatorname{adj} A) = |A|\,I⁠. Basics: why the inverse divides by |A|

5Two lines meet once when ∣A∣≠0|A| \ne 0

∣A∣≠0|A| \ne 0 means the two lines are not parallel, so they cross at exactly one point. Basics: two lines, cross, parallel or the same

Solution

  1. Write the system as AX=BAX = B

    A=[5232],X=[xy],B=[35].A = \begin{bmatrix} 5 & 2 \\ 3 & 2 \end{bmatrix},\quad X = \begin{bmatrix} x \\ y \end{bmatrix},\quad B = \begin{bmatrix} 3 \\ 5 \end{bmatrix}.

    AA is 2×22\times2 and XX is 2×12\times1⁠, so AXAX is defined and is 2×12\times1⁠, like BB⁠:

    AX=[5x+2y3x+2y].AX = \begin{bmatrix} 5x + 2y \\ 3x + 2y \end{bmatrix}.

    Setting AX=BAX = B and comparing entries gives back the two equations, so AA⁠, XX and BB are right.

    Row 1 of AA holds the coefficients of the first equation, row 2 those of the second, and the columns follow the order xx⁠, then yy⁠. Any other arrangement would multiply out to different equations.
    Section 4.6.1 (matrix form of a system); Section 3.4.5 (row times column). Lesson: solving systems AX = B
  2. Compute ∣A∣|A|

    ∣A∣=∣5232∣=5(2)−2(3)=10−6=4.\begin{aligned} |A| &= \begin{vmatrix} 5 & 2 \\ 3 & 2 \end{vmatrix} = 5(2) - 2(3)\\ &= 10 - 6 = 4. \end{aligned}

    ∣A∣=4≠0|A| = 4 \ne 0⁠, so AA is nonsingular, A−1A^{-1} exists, and the system has exactly one solution, X=A−1BX = A^{-1}B⁠.

    If AX=BAX = B⁠, multiplying on the left by A−1A^{-1} gives X=A−1BX = A^{-1}B⁠, so there is no other solution; and A(A−1B)=IB=BA(A^{-1}B) = IB = B⁠, so this one does work. In the picture, the slopes are −52-\frac{5}{2} and −32-\frac{3}{2}⁠, which differ, so the lines cross once.
    Section 4.6.1, Case I; Definition 5, Section 4.5 (nonsingular). Basics: two lines
  3. Find the cofactors and adj⁡A\operatorname{adj} A

    With a11=5a_{11} = 5⁠, a12=2a_{12} = 2⁠, a21=3a_{21} = 3⁠, a22=2a_{22} = 2⁠, each minor is the single entry left after deleting a row and a column:

    A11=(−1)1+1M11=+(2)=2,A12=(−1)1+2M12=−(3)=−3,A21=(−1)2+1M21=−(2)=−2,A22=(−1)2+2M22=+(5)=5.\begin{aligned} A_{11} &= (-1)^{1+1} M_{11} = +(2) = 2,\\ A_{12} &= (-1)^{1+2} M_{12} = -(3) = -3,\\ A_{21} &= (-1)^{2+1} M_{21} = -(2) = -2,\\ A_{22} &= (-1)^{2+2} M_{22} = +(5) = 5. \end{aligned}

    Matrix of cofactors, then its transpose:

    [A11A12A21A22]=[2−3−25],\begin{bmatrix} A_{11} & A_{12} \\ A_{21} & A_{22} \end{bmatrix} = \begin{bmatrix} 2 & -3 \\ -2 & 5 \end{bmatrix}, adj⁡A=[A11A21A12A22]=[2−2−35].\operatorname{adj} A = \begin{bmatrix} A_{11} & A_{21} \\ A_{12} & A_{22} \end{bmatrix} = \begin{bmatrix} 2 & -2 \\ -3 & 5 \end{bmatrix}.

    Shortcut check: swap 5 and 2 on the diagonal, change the signs of 2 and 3: the same matrix.

    M12M_{12} is found by deleting row 1 and column 2, which leaves a21=3a_{21} = 3⁠; its cofactor carries the sign (−1)3=−1(-1)^{3} = -1⁠. Then the transpose sends A12=−3A_{12} = -3 to row 2, column 1 of the adjoint.
    Definitions 1 and 2, Section 4.4; Definition 3 and the Remark after Example 12, Section 4.5.1. Basics: the sign pattern
  4. Form A−1A^{-1} and check AA−1=IAA^{-1} = I

    A−1=1∣A∣adj⁡A=14[2−2−35].A^{-1} = \frac{1}{|A|}\operatorname{adj} A = \frac{1}{4}\begin{bmatrix} 2 & -2 \\ -3 & 5 \end{bmatrix}.

    Check A(adj⁡A)A(\operatorname{adj} A)⁠, entry by entry:

    (1,1): 5(2)+2(−3)=10−6=4,(1,2): 5(−2)+2(5)=−10+10=0,(2,1): 3(2)+2(−3)=6−6=0,(2,2): 3(−2)+2(5)=−6+10=4.\begin{aligned} (1,1)&:\ 5(2) + 2(-3) = 10 - 6 = 4,\\ (1,2)&:\ 5(-2) + 2(5) = -10 + 10 = 0,\\ (2,1)&:\ 3(2) + 2(-3) = 6 - 6 = 0,\\ (2,2)&:\ 3(-2) + 2(5) = -6 + 10 = 4. \end{aligned} A(adj⁡A)=[4004]=4I,A(\operatorname{adj} A) = \begin{bmatrix} 4 & 0 \\ 0 & 4 \end{bmatrix} = 4I,

    so AA−1=14(4I)=IAA^{-1} = \frac{1}{4}(4I) = I⁠.

    Theorem 1 predicts ∣A∣=4|A| = 4 on the diagonal and 0 elsewhere. Getting exactly that confirms the cofactors before we use them.
    Theorem 1 and Theorem 4, Section 4.5. Basics: why the inverse divides by |A|
  5. Compute X=A−1BX = A^{-1}B

    A−1A^{-1} (2×22\times2⁠) times BB (2×12\times1⁠) is 2×12\times1⁠. First (adj⁡A)B(\operatorname{adj} A)B⁠:

    row 1: 2(3)+(−2)(5)=6−10=−4,row 2: (−3)(3)+5(5)=−9+25=16.\begin{aligned} \text{row 1}&:\ 2(3) + (-2)(5)\\ &= 6 - 10 = -4,\\ \text{row 2}&:\ (-3)(3) + 5(5)\\ &= -9 + 25 = 16. \end{aligned} X=[xy]=14[−416]=[−14].X = \begin{bmatrix} x \\ y \end{bmatrix} = \frac{1}{4}\begin{bmatrix} -4 \\ 16 \end{bmatrix} = \begin{bmatrix} -1 \\ 4 \end{bmatrix}.

    Comparing entries, x=−1x = -1⁠, y=4y = 4.

    X=A−1BX = A^{-1}B comes from multiplying AX=BAX = B on the left by A−1A^{-1}⁠, so A−1A^{-1} stays on the left. The 14\frac{1}{4} is applied last, and here it divides both entries exactly.
    Equality of matrices, Section 3.3.1. Basics: rows, columns and positions
  6. Check in both original equations

    5x+2y=5(−1)+2(4)=−5+8=3,3x+2y=3(−1)+2(4)=−3+8=5.\begin{aligned} 5x + 2y &= 5(-1) + 2(4) = -5 + 8 = 3,\\ 3x + 2y &= 3(-1) + 2(4) = -3 + 8 = 5. \end{aligned}

    Both hold, so (−1,4)(-1, 4) is the solution.

    The point must lie on both lines; checking only one equation would not show that.
−3−2−1012−2−101234567 xy 5x + 2y = 3 3x + 2y = 5 (−1, 4)
The two lines have slopes −52-\frac{5}{2} and −32-\frac{3}{2}⁠. Because the slopes differ (∣A∣=4≠0|A| = 4 \ne 0⁠), they meet at exactly one point, (−1,4)(-1, 4)⁠.
Result

∣A∣=4≠0|A| = 4 \ne 0⁠, so AA is invertible with

A−1=14[2−2−35],A^{-1} = \frac{1}{4}\begin{bmatrix} 2 & -2 \\ -3 & 5 \end{bmatrix},

and the unique solution is x=−1x = -1⁠, y=4y = 4.

(Textbook answer: x=−1x = -1⁠, y=4y = 4⁠.)

Check it with numbers

The two equations have the same yy-term 2y2y⁠, so subtracting the second from the first removes yy at once: (5x+2y)−(3x+2y)=3−5(5x + 2y) - (3x + 2y) = 3 - 5⁠, that is 2x=−22x = -2⁠, so x=−1x = -1⁠. Then 2y=3−5(−1)=82y = 3 - 5(-1) = 8⁠, so y=4y = 4⁠. The elimination method gives the same answer as the matrix method.

Common mistakes
  1. Forgetting to transpose. Using the cofactor matrix (rows 2,−32, -3 and −2,5-2, 5⁠) in place of the adjoint gives x=14(6−15)=−94x = \frac{1}{4}(6 - 15) = -\frac{9}{4} and y=14(−6+25)=194y = \frac{1}{4}(-6 + 25) = \frac{19}{4}⁠, which fail the first equation: 5x+2y=−745x + 2y = -\frac{7}{4}⁠, not 3.
  2. Swapping the wrong pair in the shortcut. The diagonal entries 5 and 2 swap; the off-diagonal entries 2 and 3 keep their places and only change sign.
  3. Multiplying in the wrong order. X=A−1BX = A^{-1}B⁠; the product BA−1BA^{-1} is not even defined.
What to take away
  1. Matrix method: AX=BAX = B⁠, check ∣A∣≠0|A| \ne 0⁠, A−1=1∣A∣adj⁡AA^{-1} = \frac{1}{|A|}\operatorname{adj} A⁠, X=A−1BX = A^{-1}B⁠, check.
  2. Confirm the adjoint with A(adj⁡A)=∣A∣ IA(\operatorname{adj} A) = |A|\,I before using it. Four products for a 2×22\times2 matrix is a small price for certainty.
  3. When a quicker route exists (here, subtracting the equations), use it as an independent check.

Every fact used, and where it comes from

FactUsed inSource
A system written as AX=BAX = BStep 1Section 4.6.1 (Lesson: solving systems)
Matrix product, row times columnSteps 1, 4, 5Section 3.4.5 (Chapter 3)
2×22\times2 determinant =ad−bc= ad - bcStep 2Section 4.2.2 (Lesson: determinant)
Nonsingular: ∣A∣≠0|A| \ne 0⁠; then X=A−1BX = A^{-1}B is the unique solutionSteps 2, 5Definition 5, Section 4.5; Section 4.6.1, Case I
Minor, cofactor Aij=(−1)i+jMijA_{ij} = (-1)^{i+j}M_{ij}Step 3Definitions 1 and 2, Section 4.4 (Lesson: minors and cofactors)
adj⁡A\operatorname{adj} A and the 2×22\times2 shortcutStep 3Definition 3 and the Remark after Example 12, Section 4.5.1 (Lesson: the adjoint)
A(adj⁡A)=∣A∣ IA(\operatorname{adj} A) = |A|\,I⁠; A−1=1∣A∣adj⁡AA^{-1} = \frac{1}{|A|}\operatorname{adj} AStep 4Theorems 1 and 4, Section 4.5 (Lesson: inverse of a matrix)
Equality of matricesSteps 1, 5Section 3.3.1 (Chapter 3)
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