Step 1: Let the eigenvector be
\[
v =
\begin{bmatrix}
2\alpha \\
\alpha
\end{bmatrix}
= \alpha
\begin{bmatrix}
2 \\
1
\end{bmatrix}
\]
Since an eigenvector is defined up to a scalar multiple, we may ignore \( \alpha \) and take
\[
v =
\begin{bmatrix}
2 \\
1
\end{bmatrix}
\]
Step 2: Use the eigenvector property.
If \( v \) is an eigenvector of matrix \( A \), then
\[
A v = \lambda v
\]
Given
\[
A =
\begin{bmatrix}
1 & 1 \\
-4 & x
\end{bmatrix}
\]
Compute \( A v \):
\[
A
\begin{bmatrix}
2 \\
1
\end{bmatrix}
=
\begin{bmatrix}
1(2) + 1(1) \\
-4(2) + x(1)
\end{bmatrix}
=
\begin{bmatrix}
3 \\
-8 + x
\end{bmatrix}
\]
Step 3: Equate with \( \lambda v \).
\[
\begin{bmatrix}
3 \\
-8 + x
\end{bmatrix}
=
\lambda
\begin{bmatrix}
2 \\
1
\end{bmatrix}
\]
This gives the system:
\[
3 = 2\lambda
\]
\[
-8 + x = \lambda
\]
Step 4: Solve for \( x \).
From the first equation:
\[
\lambda = \frac{3}{2}
\]
Substitute into the second equation:
\[
-8 + x = \frac{3}{2}
\Rightarrow x = \frac{19}{2}
\]
Final Answer:
\[
x = \frac{19}{2}
\]