multinomial

in statistics, a multinomial distribution is used to model outcomes with more than two categories.

we can apply the multinomial theorem to expand expressions involving powers of sums.

multinomial logistic regression is useful for predicting outcomes with multiple categories.

researchers often use multinomial models to analyze survey data.

the multinomial coefficient counts the number of ways to distribute indistinguishable objects into distinct boxes.

understanding multinomial distributions is crucial for advanced statistical analysis.

in machine learning, multinomial naive bayes classifiers are commonly used for text classification.

we need to calculate the probabilities using the multinomial formula for this experiment.

the multinomial distribution can be derived from the binomial distribution under certain conditions.

students should familiarize themselves with the properties of multinomial expressions for their exams.