Answer
$L=52.7n+486.3$
Work Step by Step
Using desmos.com, we enter a table (columns labeled as $x_{1},y_{1}$). Then, we enter the data points, and in a new cell, enter$\quad y_{1}\sim mx_{1}+b$
The calculator returns $\left\{\begin{array}{l}
m=52.7\\
b=486.3\\
r=0.9931
\end{array}\right.$
where
$m=\displaystyle \frac{n(\sum xy)-(\sum x)(\sum y)}{n(\sum x^{2})-(\sum x)^{2}}\qquad b=\frac{\sum y-m(\sum x)}{n},$
and the $r$ is the regression cofficient
$\displaystyle \quad r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{n(\sum x^{2})-(\sum x)^{2}}\cdot\sqrt{n(\sum y^{2})-(\sum y)^{2}}}$
$r$ is close to 1, indicating a good fit for the data.
Replace
$x_{1}\leftrightarrow n$, the independent variable,
$y_{1}\leftrightarrow L$,
The regression line is given by
$L=52.7n+486.3$
