Multinomial coefficient or stars and bars for $k$ sided dice rolls

combinatoricsdicemultinomial-coefficientsprobability distributions

The wikipedia page for the multinomial distribution says it can represent the probability of counts for each side of a $k$-sided dice rolled $n$ times. But this StackExchange answer says the same quantity is counted using stars and bars. Which is right, or how are the quantities being counted differently in a way I'm not seeing?

To me it seems that the counts for each side of a $k$ sided dice rolled $n$ times should be done using stars and bars as per the logic of the SE answer, and not the multinomial coefficient.

The application of the multinomial coefficient $\frac{n}{x_1!x_2!…x_k!}$ that I'm aware of is counting counting the number of strings with repeated letters, e.g. the number of rearrangements of MISSISSIPPI is $\frac{11!}{1!4!4!2!}$.

If think of the $i$th letter as indicating the outcome of the $i$th trial, with $k$ possible letters for $k$ different possible outcomes, then these strings represent sequences of outcomes of each trial. The multinomial coefficient counts these sequences, but shouldn't we be counting the number of occurrences of each outcome while ignoring the order? For example, the multinomial coefficient distinguishes between the sequences $abca$ and $aabc$. To be invariant to the order, we need to use stars and bars?

Best Answer

Note that the Wikipedia article talks about the probability of counts for each side of a $k$-sided dice rolled $n$ times. When you roll a die, its chances of landing in each of $1-6$ is equiprobable, and the multinomial coefficient will help to give the probability for a particular pattern of throws.

For example, a pattern of $2,1,2,1,1,0,1,2,$ will have a probability of $\dfrac{\dbinom{10}{2,1,2,1,1,0,1,2}}{6^{10}}$

Stars and bars instead gives all possible ways of filling $1-6$, but these are not equiprobable, eg you can understand that if you roll a die $10$ times, getting all ten as $6's$ is much less probable than a more even distribution