- #1

- 2

- 0

error(sum_B)^2 = error(sum_total)^2 * (d(sum_B) / d(sum_total))^2 + error(sum_A)^2 * (d(sum_B) / d(sum_A))^2 + 2 * cov(sum_A, sum_total) * (d(sum_B) / d(sum_total)) * (d(sum_B) / d(sum_A))

This is simple, if I only knew the covariance of sum_A and sum_total. I have no idea of how to determine this covariance, someone else?

Or in other words: I have a series of numbers x that follow the formula x

*= p*

*- q**. How do I determine cov(sum(p) - sum(q))? Where the summing is done over all i between 0 and n.*