Cramer's Rule is a method for solving linear systems where the number of equations equals the number of variables. This means the coefficient matrix will be square: 2×2, 3×3, 4×4, and so on.
Cramer's Rule is particularly valuable in computer systems because its algorithms are clear and systematic. We can program the solution method into clear computer algorithms or codes, allowing the computer to proceed step by step until it reaches the final solution.
Let's solve a 3×3 system using Cramer's Rule. We have three equations with three variables, so the coefficient matrix will be 3×3:
Notice that we have three equations and the number of equations equals the number of variables. This means we can solve this system using Cramer's Rule.
From our system, we extract the coefficient matrix and calculate its determinant using the 3×3 determinant method we learned in previous lessons.
Now we can set up the Cramer's Rule formulas for our three variables. Each variable equals a specific determinant divided by the main determinant:
Now we need to determine what matrices to use for ,
, and
.
For , we replace the entire x-column with the constants from the right side of our equations.
Original coefficient matrix:
Replace the x-column with constants (-14, 47, 15):
Calculate the 3×3 determinant:
Therefore:
For , we replace the y-column with the constants from the right side.
Replace the y-column with constants (-14, 47, 15):
Calculate the 3×3 determinant:
Therefore:
Finally, for , we replace the z-column with the constants.
Replace the z-column with constants (-14, 47, 15):
Calculate the 3×3 determinant:
Therefore:
Let's summarize our complete solution and verify it works in all three original equations.
1️⃣ Cramer's Rule works when #equations = #variables (square coefficient matrix)
2️⃣ It provides clear algorithms ideal for computer implementation
3️⃣ For 3×3 systems: extract coefficient matrix and calculate D using 3×3 methods
4️⃣ Replace columns systematically: x-column for D_x, y-column for D_y, z-column for D_z
5️⃣ Each variable = (its determinant) ÷ (main determinant)