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Chapter 4 · Determinants

Exercise 4.5 · Q7: Solve 5x+2y=45x+2y=4⁠, 7x+3y=57x+3y=5 by the matrix method

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

Solve the system of linear equations, using matrix method.

5x+2y=47x+3y=5\begin{aligned} 5x+2y&=4\\ 7x+3y&=5 \end{aligned}
Exam answer

The system is AX=BAX = B⁠, where

A=[5273],X=[xy], B=[45]\begin{aligned} A &= \begin{bmatrix} 5 & 2 \\ 7 & 3 \end{bmatrix}, \\ X &= \begin{bmatrix} x \\ y \end{bmatrix},\ B = \begin{bmatrix} 4 \\ 5 \end{bmatrix} \end{aligned} ∣A∣=∣5273∣=15−14=1|A| = \begin{vmatrix} 5 & 2 \\ 7 & 3 \end{vmatrix} = 15 - 14 = 1

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

adj⁡A=[3−2−75]A−1=1∣A∣adj⁡A=[3−2−75]\begin{aligned} \operatorname{adj}A &= \begin{bmatrix} 3 & -2 \\ -7 & 5 \end{bmatrix} \\ A^{-1} &= \frac{1}{|A|}\operatorname{adj}A \\ &= \begin{bmatrix} 3 & -2 \\ -7 & 5 \end{bmatrix} \end{aligned} X=A−1B=[3−2−75][45]=[12−10−28+25]=[2−3]\begin{aligned} X &= A^{-1}B \\ &= \begin{bmatrix} 3 & -2 \\ -7 & 5 \end{bmatrix}\begin{bmatrix} 4 \\ 5 \end{bmatrix} \\ &= \begin{bmatrix} 12 - 10 \\ -28 + 25 \end{bmatrix} \\ &= \begin{bmatrix} 2 \\ -3 \end{bmatrix} \end{aligned}

∴ x=2, y=−3\therefore\ x = 2,\ y = -3⁠.

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

The one idea this problem is built on

The matrix method turns two equations into one: AX=BAX = B⁠. If ∣A∣≠0|A| \ne 0⁠, multiplying on the left by A−1A^{-1} isolates the unknowns, X=A−1BX = A^{-1}B⁠, exactly as dividing both sides of 5x=105x = 10 by 5 isolates xx⁠. Here ∣A∣=15−14=1|A| = 15 - 14 = 1⁠, so A−1A^{-1} is simply adj⁡A\operatorname{adj}A⁠, with whole-number entries, and the solution is x=2x = 2⁠, y=−3y = -3⁠.

Given, to find, and the plan
Given
Two linear equations in xx and yy⁠.
To find
xx and yy⁠, using the matrix method (the inverse of the coefficient matrix).
Plan
(1) Write AX=BAX = B⁠. (2) Compute ∣A∣|A| and confirm it is not 0. (3) Find the cofactors and adj⁡A\operatorname{adj}A⁠. (4) Form A−1A^{-1} and check AA−1=IAA^{-1} = I⁠. (5) Compute X=A−1BX = A^{-1}B⁠. (6) Check in both equations.

Basics you need

1Why X=A−1BX = A^{-1}B

From AX=BAX = B⁠: A−1(AX)=A−1BA^{-1}(AX) = A^{-1}B⁠, then (A−1A)X=A−1B(A^{-1}A)X = A^{-1}B by associativity, then IX=XIX = X⁠. Pre-multiplying is essential: matrix products depend on order. Basics: why the inverse divides by |A|

2The 2×22\times2 determinant

For order 2 (Section 4.2.2):

∣abcd∣=ad−cb.\begin{vmatrix}a&b\\c&d\end{vmatrix}=ad-cb.

Basics: where the determinant comes from

3The adjoint of a 2×22\times2 matrix

Swap the two diagonal entries and change the signs of the other two (Remark after Example 12). This is the transpose of the matrix of cofactors. Basics: transpose and identity

4Row times column

A 2×22\times2 matrix times a 2×12\times1 column gives a 2×12\times1 column; each entry is a row times the column. Basics: matrix facts the chapter uses

Solution

  1. Write the system as AX=BAX = B

    A=[5273]X=[xy],B=[45]\begin{gathered} A=\begin{bmatrix}5&2\\7&3\end{bmatrix}\\ X=\begin{bmatrix}x\\y\end{bmatrix},\quad B=\begin{bmatrix}4\\5\end{bmatrix} \end{gathered}

    AA is 2×22\times2 and XX is 2×12\times1⁠, so AXAX is a 2×12\times1 column:

    AX=[5⋅x+2⋅y7⋅x+3⋅y]=[5x+2y7x+3y].AX=\begin{bmatrix}5\cdot x+2\cdot y\\7\cdot x+3\cdot y\end{bmatrix}=\begin{bmatrix}5x+2y\\7x+3y\end{bmatrix}.

    So AX=BAX = B is the given system.

    Equal matrices have equal entries, so the one matrix equation holds exactly when both equations hold. Multiplying out AXAX confirms the coefficients are in the right places.
  2. Compute ∣A∣|A|

    ∣A∣=∣5273∣=5⋅3−7⋅2=15−14=1\begin{aligned} |A|&=\begin{vmatrix}5&2\\7&3\end{vmatrix}=5\cdot3-7\cdot2\\ &=15-14=1 \end{aligned}

    ∣A∣=1≠0|A| = 1 \ne 0⁠, so AA is non-singular, A−1A^{-1} exists, and the system has exactly one solution (Section 4.6.1, Case I).

    The matrix method only works when A−1A^{-1} exists, and Theorem 4 says that happens exactly when ∣A∣≠0|A| \ne 0⁠. So this check comes before anything else.
  3. Cofactors and adj⁡A\operatorname{adj}A

    For order 2, each minor is the single entry left after deleting a row and a column; then Aij=(−1)i+jMijA_{ij} = (-1)^{i+j}M_{ij}⁠:

    A11=(−1)1+1(3)=3A12=(−1)1+2(7)=−7A21=(−1)2+1(2)=−2A22=(−1)2+2(5)=5\begin{aligned} A_{11}&=(-1)^{1+1}(3)=3\\ A_{12}&=(-1)^{1+2}(7)=-7\\ A_{21}&=(-1)^{2+1}(2)=-2\\ A_{22}&=(-1)^{2+2}(5)=5 \end{aligned} adj⁡A=[A11A21A12A22]=[3−2−75]\operatorname{adj}A=\begin{bmatrix}A_{11}&A_{21}\\A_{12}&A_{22}\end{bmatrix}=\begin{bmatrix}3&-2\\-7&5\end{bmatrix}
    The transpose puts A21=−2A_{21} = -2 in row 1, column 2, and A12=−7A_{12} = -7 in row 2, column 1. The shortcut agrees: swap 5 and 3, change the signs of 2 and 7.
    Definition 3 and the Remark after Example 12, Section 4.5.1. Lesson: the adjoint
  4. A−1A^{-1}⁠, and the check AA−1=IAA^{-1} = I

    A−1=1∣A∣adj⁡A=11[3−2−75]=[3−2−75]\begin{aligned} A^{-1}&=\frac{1}{|A|}\operatorname{adj}A=\frac{1}{1}\begin{bmatrix}3&-2\\-7&5\end{bmatrix}\\ &=\begin{bmatrix}3&-2\\-7&5\end{bmatrix} \end{aligned}

    Row of AA times column of A−1A^{-1}⁠:

    (1,1): 5(3)+2(−7)=15−14=1(1,2): 5(−2)+2(5)=−10+10=0(2,1): 7(3)+3(−7)=21−21=0(2,2): 7(−2)+3(5)=−14+15=1\begin{aligned} (1,1)&:\ 5(3)+2(-7)=15-14=1\\ (1,2)&:\ 5(-2)+2(5)=-10+10=0\\ (2,1)&:\ 7(3)+3(-7)=21-21=0\\ (2,2)&:\ 7(-2)+3(5)=-14+15=1 \end{aligned}

    So AA−1=IAA^{-1} = I⁠. ✓

    Because ∣A∣=1|A| = 1⁠, dividing by ∣A∣|A| changes nothing, and the inverse has whole-number entries. The product check shows the inverse is right before we use it.
    A−1=1∣A∣adj⁡AA^{-1} = \frac{1}{|A|}\operatorname{adj}A⁠, Theorem 4. Lesson: inverse of a matrix
  5. The solution X=A−1BX = A^{-1}B

    X=A−1B=[3−2−75][45]X=A^{-1}B=\begin{bmatrix}3&-2\\-7&5\end{bmatrix}\begin{bmatrix}4\\5\end{bmatrix} x=3(4)+(−2)(5)=12−10=2y=(−7)(4)+5(5)=−28+25=−3\begin{aligned} x&=3(4)+(-2)(5)=12-10=2\\ y&=(-7)(4)+5(5)=-28+25=-3 \end{aligned}

    So x=2x = 2⁠, y=−3y = -3⁠.

    A−1A^{-1} is 2×22\times2 and BB is 2×12\times1⁠, so XX is 2×12\times1⁠: its first entry is xx⁠, its second yy⁠. The order A−1BA^{-1}B matters; BA−1BA^{-1} is not even defined.
    Section 4.6.1, Case I. Lesson: solving systems AX = B
  6. Check in both equations

    5x+2y=5(2)+2(−3)=10−6=4 ✓7x+3y=7(2)+3(−3)=14−9=5 ✓\begin{aligned} 5x+2y&=5(2)+2(-3)=10-6=4\ \checkmark\\ 7x+3y&=7(2)+3(-3)=14-9=5\ \checkmark \end{aligned}
    0 1 2 3 4 −8 −7 −6 −5 −4 −3 −2 −1 0 1 2 x y P 5x + 2y = 4 7x + 3y = 5 P = (2, −3) slopes −5/2 and −7/3: close, but different, so one crossing point
    The slopes are −52-\tfrac52 and −73-\tfrac73⁠: different, so the lines meet exactly once, at P=(2,−3)P = (2, -3)⁠. They are close, so the lines cross at a very small angle (about 1.4∘1.4^\circ⁠).
    Substituting into the original equations, not into the matrices, catches any mistake made in setting up AA and BB as well as in the arithmetic.
Result

x=2x = 2⁠, y=−3y = -3⁠. (Textbook answer: x=2x = 2⁠, y=−3y = -3⁠.)

Check it with numbers

Eliminate xx by hand: 7 times the first equation is 35x+14y=2835x + 14y = 28⁠, and 5 times the second is 35x+15y=2535x + 15y = 25⁠. Subtracting, −y=3-y = 3⁠, so y=−3y = -3⁠; then 5x=4−2y=105x = 4 - 2y = 10⁠, so x=2x = 2⁠. Same answer.

Common mistakes
  1. Writing X=BA−1X = BA^{-1}⁠. A 2×12\times1 times a 2×22\times2 is not defined; A−1A^{-1} must be on the left.
  2. Swapping the wrong entries for the adjoint. The diagonal entries 5 and 3 swap; the off-diagonal 2 and 7 stay in place but change sign.
  3. Skipping the ∣A∣≠0|A| \ne 0 check. Without it, there is no guarantee A−1A^{-1} exists.
What to take away
  1. Matrix method: AX=BAX = B⁠, check ∣A∣≠0|A| \ne 0⁠, then X=A−1B=1∣A∣(adj⁡A)BX = A^{-1}B = \frac{1}{|A|}(\operatorname{adj}A)B⁠.
  2. For order 2 the adjoint is quick: swap the diagonal, negate the rest.
  3. Always substitute the answer back into the original equations.

Every fact used, and where it comes from

FactUsed inSource
A system as AX=BAX = B⁠; X=A−1BX = A^{-1}B when ∣A∣≠0|A| \ne 0Steps 1, 2, 5Section 4.6.1, Case I (Lesson: solving systems AX = B)
2×22\times2 determinant =ad−cb= ad - cbStep 2Section 4.2.2
Aij=(−1)i+jMijA_{ij} = (-1)^{i+j}M_{ij}Step 3Definitions 1, 2, Section 4.4
Adjoint = transpose of the cofactor matrix; order 2 shortcutStep 3Definition 3 and Remark, Section 4.5.1
AA invertible   ⟺  ∣A∣≠0\iff |A| \ne 0⁠; A−1=1∣A∣adj⁡AA^{-1} = \frac{1}{|A|}\operatorname{adj}ASteps 2, 4Theorem 4, Section 4.5
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