Step 1: Set up the general line.
A straight line through the data can be written as $y = mx + c$, where $m$ is the slope and $c$ is the value of $y$ when $x=0$.
Step 2: Read $c$ straight off the table.
When the year $x=0$, the table already gives $y=0.1$. So $c=0.1$ without any extra work.
Step 3: Get $m$ from the two ends of the table.
Using the first point $(0, 0.1)$ and the last point $(40, 0.5)$,
\[ m=\frac{0.5-0.1}{40-0}=\frac{0.4}{40}=0.01 \]
Step 4: Write the fitted line.
\[ y=0.01x+0.1 \]
Step 5: Confirm with a middle row, not just the ends.
At $x=20$, the formula gives $y=0.01(20)+0.1=0.3$, exactly the value the table shows. This confirms the fit is not a coincidence of the endpoints.
Step 6: Reject the flipped options.
Options that write $x$ in terms of $y$, like $x=y+0.1$ or $x=0.1+0.01y$, mix up which variable is doing the changing. Since year is the input and allele frequency is the output here, $y$ should be written in terms of $x$, not the other way round, and neither flipped option even satisfies the table's numbers when tested directly.
Step 7: Conclude.
\[ \boxed{y=0.01x+0.1} \]