Solutions to systems of equations come in three types:
\[ x + y = 2 \] \[ x + y = 4 \] There is no solution to this system of equations because you can not find two numbers that add to make \(2\) and \(4\) simultaneously. If you were to proceed with attempting to solve the system, you end up with a contradictory statement - for example, \( 0 = 2 \), or \(4 = 2\).
These three cases can be represented graphically as follows:
In discussing the use of Gaussian elimination in solving a system of equations, we will use the following system of equations and as example:
\[ 2x-3y+3z=6 \]
\[ x+2y-z=3 \]
\[ x-y+z=2 \]
In order to solve a system of equations using Gaussian Elimination, the system must first be transformed into an augmented matrix:
$$ \left[ \begin{array}{ccc|c} 2 & -3 & 3 & 6 \\ 1 & 2 & -1 & 3 \\ 1 & -1 & 1 & 2\\ \end{array} \right] $$
There are three operations you are allowed to perform on an augmented matrix when using Gaussian elimination:
Elementary Row Operations:
These operations mirror operations you can use on the system of equations closely; take a look at the side-by-side comparisons below:
When performing Gaussian elimination, the goal is to convert the augmented matrix into row echelon form. Below are the conditions required for a matrix to be in row echelon form:
Row Echelon Form:
Any row of zeros are below the rows of leading \(1\)'s
Notice that the operations above that we have chosen have led us toward row echelon form. Below are the rest of the operations required to do so. Read them carefully and make sure you understand how and why each operation was taken.
Now that the matrix is in row echelon form, it can be converted back into a system of equations and solved.
$$ \begin{align*} x + 2y - z &= 3 \\ y - z &= -2 \\ z &= 7 \end{align*} $$
\(z = 7\) has been solved, so subbing this into the second equation gives
\[ y - 7 = -2 \qquad \implies \qquad y = 5 \]
Now that we have \(z = 7\) and \(y = 5\), both can be subbed into the first equation to solve for \(x\).
\[ x + 2(5) - 7 = 3 \qquad \implies \qquad x = 0 \]
Now the system has been solved -- the unique solution to the system is
$$ \begin{align*} x &= 0\\ y &= 5 \\ z &= 7 \end{align*} $$
See the video below for another example of Gaussian elimination.
We can also solve systems of linear equations algebraically by substitution. We use the following system of equations as an example:
\(2x+4y=12\) \((1)\)
\(6x-2y=8\) \((2)\)
We first isolate for \(x\) in equation \((1)\) so we can use it in the substitution step:
\(2x+4y=12\)
\(\implies2x=12-4y\)
\(\implies x=\frac{12-4y}{2}\)
\(\implies x=\frac{2(6-2y)}{2}\)
\(\implies x=6-2y\) \((*)\)
Then, we can substitute the equation \((*)\) into equation \((2)\) to find \(y\):
\(6x-2y=8\)
\(\implies 6(6-2y)-2y=8\)
\(\implies 36-12y-2y=8\)
\(\implies 36-8=12y+2y\)
\(\implies 28=14y\)
\(\implies y=2\)
Now, we can substitute \(y=2\) into the equation \((*)\) to solve for \(x\):
\(x=6-2y\)
\(\implies x=6-2(2)\)
\(\implies x=6-4\)
\(\implies x=2\)
So the unique solution to this system is:
\(x=2\)
\(y=2\)