NumPy Tutorial · NumPy Random
Multinomial Distribution
Learn all about Multinomial Distribution in this comprehensive tutorial.
5 min read advanced
- •Multinomial distribution is a generalization of binomial distribution.
Multinomial Distribution
Multinomial distribution is a generalization of binomial distribution.
It describes outcomes of multi-nomial scenarios unlike binomial where scenarios must be only one of two. e.g. Blood type of a population, dice roll outcome.
It has three parameters:
n - number of times to run the experiment.
pvals - list of probabilties of outcomes (e.g. [1/6, 1/6, 1/6, 1/6, 1/6, 1/6] for dice roll).
size - The shape of the returned array.
python
Note: Note: Multinomial samples will NOT produce a single value!
They will produce one value for each pval.
Note: Note: As they are generalization of binomial distribution their visual representation and similarity of normal distribution is same as that of multiple binomial distributions.
Module quiz
2 questions1
Which of the following is true about Multinomial Distribution?
2
What is the most common pitfall when working with Multinomial Distribution?
Answer all questions to submit.