Multinomial Distribution Example. A multinomial experiment will have a multinomial distribution. Three card players play a series of matches.
3 Frequency Counts From A Multinomial Distribution With Four Categories Download Table from www.researchgate.net
The multinomial distribution can be used to compute the probabilities in situations in which there are more than two possible outcomes. 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. Bayes rule can be used to determine the probability of an event or outcome as mentioned above.
Three card players play a series of matches.
For example suppose that two chess players had played numerous games and it was determined that the probability that player a would win is 0 40 the probability that player b would win is 0 35 and the probability that the game would end in a draw is 0 25. Bayes rule can be used to determine the probability of an event or outcome as mentioned above. For example bayes rule can be used to predict the pressure of a system given the temperature and statistical data for the system. For n independent trials each of which leads to a success for exactly one of k categories with each category having a given fixed success probability the multinomial distribution gives the.
