In this paper An Improved Algorithm for Decentralized Extrema-Finding in Circular Configurations of Processes from 1979, in chapter with analyze of average number of passes messages I found this equation:
$$\sum_{i=k}^{n-1}k \frac{{i-1}\choose{k-1}}{{n-1}\choose{k-1}} \times \frac{n-i}{n-k} = \frac{n}{k+1}$$
Can anyone explain me why it's equal and how can I calculate it?
In paper they write only that this left side "can be simplified to" right side.
Edit 1: I think that main problem is to understand what this sum is: $$\sum_{i=k}^{n-1} {{i-1}\choose{k-1}} \times (n-i)$$ WolframAlpha.
Because:
$$\sum_{i=k}^{n-1}k \frac{{i-1}\choose{k-1}}{{n-1}\choose{k-1}} \times \frac{n-i}{n-k} = \frac{k}{{{n-1}\choose{k-1}}(n-k)} \sum_{i=k}^{n-1} {{i-1}\choose{k-1}} \times (n-i)$$
And according to WolframAlpha: $$\sum_{i=k}^{n-1} {{i-1}\choose{k-1}} \times (n-i) = \frac{n(n-k){{n-1}\choose{k-1}}}{k(k+1)} $$
So everything could be nicely reduced.
Have you seen this formula, sometimes known as the hockey-stick formula $$\sum_{i=k}^{n-1}{i-1\choose k-1}={n-1\choose k}$$ It is proved by identifying the binomial coefficients in Pascal's triangle, noting that ${k-1\choose k-1}={k\choose k}$, and cascading down the diagonal.
Another relevant formula is $i{i-1 \choose k-1} = k{i\choose k}$. Put them together and you get $$(n-i){i-1\choose k-1} = n{i-1\choose k-1} - k{i\choose k}$$ then sum them up separately.