Expected number of observed categories ($\mathbb{E}{K}_n={\sum }_{j=1}^m(1-(1-p_j{)}^n)$)

In $n$ independent trials with category probabilities $p_1,\dots ,p_m$, let $K_n$ count the distinct categories observed. Write it as the sum of indicator random variables for the categories' appearances. Category $j$ is absent with probability $(1-p_j{)}^n$, so linearity of expectation gives the displayed formula. The appearance indicators need not be independent. For equally likely categories the expression becomes $m(1-(1-1/m{)}^n)$; uneven probabilities can substantially delay observation of rare categories.