R depends on L, W, rho and xj.
If the errors of those 4 parameters are statistically independent, then the variance of R will be the sum of the variances of those 4 parameters, hence the summation.
Another way to look at it is by taking partial derivatives of R with respect to each parameter, then dividing by R and squaring. Then you can add it up all together because all variations are statistically independent. Otherwise you couldn't just add them up, you should take into account any cross-correlation between parameters.
And just in case you're wondering how it's possible to add errors that are in the denominator of the equation (parameters W and xj): we can do it because there is a first order approximation involved.
$$ \frac{1}{W} \approx -W \text{ if } \vert{W}\rvert \ll 1 $$