Multinomial Distribution Equation. By marco taboga phd. If you perform times an experiment that can have only two outcomes either success or failure then the number of times you obtain one of the two outcomes success is a binomial random variable.
N 2 2 number won by player b n 3 3 the number drawn p 1 0 40 probability player a wins p 2 0 35 probability player b wins p 3 0 25 probability of a draw the formula for k outcomes is. We can also use a range as the argument of multinomial as in figure 1. The examples below illustrate how to use the multinomial formula to compute the probability of an outcome from a multinomial experiment.
In probability theory the multinomial distribution is a generalization of the binomial distribution for example it models the probability of counts for each side of a k sided die rolled n times.
Probability and distributions formulas list online. X 1 x k thus we could also calculate the answer to example 9 10 by using the formula. Note that the binomial distribution is a special case of the multinomial when k 2. In probability theory the multinomial distribution is a generalization of the binomial distribution for example it models the probability of counts for each side of a k sided die rolled n times.
