Consider the following formula :
$$p_i=\sum_{j=1}^n\frac{\binom{i-1}{j-1}\binom{n^2-i}{n-j}}{\binom{n^2}{n}},$$
where $i,n$ are positive integer and $i=1,\ldots,n^2$.
Suppose there are $n$ boxes (the boxes are labeled with $1,2,\ldots,n$) each containing $n$ balls. The balls in each box are ordered according to their size. The $i$th $(i=1,2,\ldots,n^2)$ smallest ball among all $n^2$ balls is the $j$th smallest ball $(j=1,2,\ldots,n)$ of a box if and only if (1) the first $(i-1)$ values contain exactly $(j-1)$ 1's. This can be done in $\binom{i-1}{j-1}$ ways, $(2)$ the $i$th value is a $1$, (3) And therefore there are exactly $(n-j)$ 1's distributed among the remaining $(n^2-i)$ values. This can be done in $\binom{n^2-i}{n-j}$ ways.
The total number of ways in which the $n^2$ balls can be randomly allocated to $n$ boxes is $\binom{n^2}{n}$.
Then the probability that the $i$th smallest ball among all $n^2$ balls is the $j$th smallest ball of a box is
$$\frac{\binom{i-1}{j-1}\binom{n^2-i}{n-j}}{\binom{n^2}{n}}.$$
We select a ball if it is the $1$st smallest ball of the $1$st box, or $2$nd smallest ball of the $2$nd box, thus $n$th smallest ball of the $n$th box. It is not possible that the $i$th smallest ball overall was in two boxes, but it had to be in some box. Therefore the event that "the $i$th smallest ball was in box $j$", is an exhaustive partition of the possibilities. Consequently there chances add up. Hence the probability that the $i$th smallest ball is selected is
$$p_i=\sum_{j=1}^n\frac{\binom{i-1}{j-1}\binom{n^2-i}{n-j}}{\binom{n^2}{n}}.$$
I expected different value of $p_i$ for different $i$. But I was astonished that the $p_i$ is same for all $i$.
It seems
$$p_i=\sum_{j=1}^n\frac{\binom{i-1}{j-1}\binom{n^2-i}{n-j}}{\binom{n^2}{n}}=\frac{1}{n}.$$
I checked it by calculating $p_i$ for different $n$ such as $2$ or $3$.
What is the reason that $p_i$ does not depend on $i$?
Why this complex formula is nothing but a uniform probability?