To solve the given system of linear equations, we can use matrix methods such as Gaussian elimination or matrix inversion. However, a straightforward approach is to use Python's numpy library, which provides a convenient function to solve systems of linear equations directly.
Step 1: Set Up the System of Equations
We are given the following system of equations:
\[
\begin{align*}
& \quad x + 7y - z = 49 \\
& \quad 2x - 5y + 2z = -28 \\
& \quad x - 6y = -32
\end{align*}
\]
Step 2: Write in Matrix Form
This system can be expressed in matrix form as \( A \mathbf{x} = B \), where:
\[
A = \begin{bmatrix}
1 & 7 & -1 \\
2 & -5 & 2 \\
1 & -6 & 0
\end{bmatrix}, \quad
\mathbf{x} = \begin{bmatrix}
x \\
y \\
z
\end{bmatrix}, \quad
B = \begin{bmatrix}
49 \\
-28 \\
-32
\end{bmatrix}
\]
Step 3: Solve for Variables
By solving the matrix equation, we find:
\[
\mathbf{x} = \begin{bmatrix}
4 \\
6 \\
-3
\end{bmatrix}
\]
This gives us the values:
\[
x = 4, \quad y = 6, \quad z = -3
\]
Final Answer
The solution to the system of equations is:
\[
\boxed{x = 4}, \quad \boxed{y = 6}, \quad \boxed{z = -3}
\]