I know that the expected value of the sum of $n$ random variables is the sum of the expectation of each one.
The expected value of a uniformly distributed random variable $U(a,b)$ is also well known
$$ \frac{b-a}{2} $$
I can also calculate the expected value of the min/max random variable in a set of $n$ random variables [1].
Is there a way to calculate the expected value of the sum of the $k$ (out of a set of $n$) smallest uniform random variables?
[1] Expectation of Minimum of n i.i.d. uniform random variables.
If $X_1,\dotsc,X_n\overset{iid}{\sim}\text{unif}(a,b)$, then $X_{(k)}$ is the $k$th order statistic and it follows a scaled beta distribution. Then if $X = X_{(1)}+\dotsb+X_{(k)}$, then $$E[X] = E[X_{(1)}]+\dotsb+E[X_{(k)}].$$
Using the transformation$~X_{(i)} = (b-a)U_{(i)}+a~$ we have \begin{align*}E[X] &= E[(b-a)U_{(1)}+a]+\dotsb+E[(b-a)U_{(k)}+a]\\ &=(b-a)\big[E[U_{(1)}]+\cdots+E[U_{(k)}]\big]+ka\\ &=(b-a)\left[\frac{1}{1+(n+1-1)}+\dotsb+\frac{k}{k+(n+1-k)}\right]+ka\\ &=(b-a)\left[\frac{1}{n+1}+\dotsb+\frac{k}{n+1}\right]+ka\\ &=\frac{b-a}{n+1}\cdot\frac{k(k+1)}{2}+ka &= \end{align*}
where $U_{(i)}\sim \text{Beta}(i, n+1-i)$.