Skip to content

Mathematics · Ch 1 — Applications of Matrices and Determinants

Cramer's Rule

1.4.3.2

Cramer's Rule

Cramer's rule applies when the coefficient matrix of AX=BAX=B is square and non-singular; for three equations in three unknowns,

a11x1+a12x2+a13x3=b1,a21x1+a22x2+a23x3=b2,a31x1+a32x2+a33x3=b3,a_{11}x_1+a_{12}x_2+a_{13}x_3=b_1,\quad a_{21}x_1+a_{22}x_2+a_{23}x_3=b_2,\quad a_{31}x_1+a_{32}x_2+a_{33}x_3=b_3,

let Δ=∣a11a12a13a21a22a23a31a32a33∣≠0\Delta=\begin{vmatrix}a_{11}&a_{12}&a_{13}\\a_{21}&a_{22}&a_{23}\\a_{31}&a_{32}&a_{33}\end{vmatrix}\ne0. Then

x1=Δ1Δ,x2=Δ2Δ,x3=Δ3Δ,x_1=\frac{\Delta_1}{\Delta},\qquad x_2=\frac{\Delta_2}{\Delta},\qquad x_3=\frac{\Delta_3}{\Delta},

where Δk\Delta_k is Δ\Delta with column kk replaced by the constants b1,b2,b3b_1,b_2,b_3 (columns ≠k\ne k unchanged). The same pattern gives x=Δ1/Δ, y=Δ2/Δx=\Delta_1/\Delta,\ y=\Delta_2/\Delta for a two-equation, two-unknown system.

Derivation idea for x1x_1. x1Δx_1\Delta equals Δ\Delta with its first column scaled by x1x_1; using the original equations, that scaled column (a11x1,a21x1,a31x1)(a_{11}x_1,a_{21}x_1,a_{31}x_1) can be rewritten as bi−ai2x2−ai3x3b_i-a_{i2}x_2-a_{i3}x_3; splitting the determinant by that sum and discarding the two pieces that repeat columns 2 or 3 (hence vanish) leaves exactly Δ1\Delta_1 -- so x1Δ=Δ1x_1\Delta=\Delta_1, and dividing by Δ≠0\Delta\ne0 gives the rule. x2,x3x_2,x_3 follow identically.

Worked illustration. Solve x1−x2=3, 2x1+3x2+4x3=17, x2+2x3=7x_1-x_2=3,\ 2x_1+3x_2+4x_3=17,\ x_2+2x_3=7. Δ=∣1−10234012∣=6≠0\Delta=\begin{vmatrix}1&-1&0\\2&3&4\\0&1&2\end{vmatrix}=6\ne0; Δ1=∣3−101734712∣=12\Delta_1=\begin{vmatrix}3&-1&0\\17&3&4\\7&1&2\end{vmatrix}=12; Δ2=∣1302174072∣=−6\Delta_2=\begin{vmatrix}1&3&0\\2&17&4\\0&7&2\end{vmatrix}=-6; Δ3=∣1−132317017∣=24\Delta_3=\begin{vmatrix}1&-1&3\\2&3&17\\0&1&7\end{vmatrix}=24. So x1=12/6=2, x2=−6/6=−1, x3=24/6=4x_1=12/6=2,\ x_2=-6/6=-1,\ x_3=24/6=4.

Word problems. A path y=ax2+bx+cy=ax^2+bx+c through three known points, or a scoring/rate/mixture problem, gives a 3×33\times3 system in the unknown constants exactly as for matrix inversion; Cramer's rule is convenient here since each unknown is found independently, without computing a full inverse. …