[수리통계학] Discrete Distributions
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1. Discrete Uniform Distribution
: When a pmf is constant on the space R of X; we say that the distribution is a discrete uniform abbreviated by DU.
2. Hypergeometric Distribution
: Suppose there are N1 success objects and N2 failure objects in a collection N = N1 + N2 of similar objects. When n objects are selected from these N objects at random with without replacement. Let the random variable X be the number of success objects among the n objects.
3. Bernoulli Distribution
: A random experiment, the outcome of which can be classified in but one of two mutually exclusive and exhaustive ways - say, success and failure. When Bernoulli experiment is performed several independent times and probability of success(p) remains the same from trial to trial. In addition, we shall frequently let q = 1 - p denote the probability of failure.
4. Binomial Distribution
: 1. A Bernoulli experiment is performed n times
2. The trials are independent
3. The probability of success on each trial is a constant p
4. The random variable X equals the number of successes in the n trials
Let X be a random variable associated with a binomial experiment, we say that X has a binomial distribution with the prob of success p.
5. Geometric Distribution
: A random experiment of observing a sequence of independent Bernoulli trials (probability of success p) until exactly the first success occur. Let X be the number of Bernoulli trials until the first success occur.
6. Negative Binomial Distribution
: A random experiment of observing a sequence of independent Bernoulli trials (probability of success p) until exactly the r-th success occur. Let X be the number of Bernoulli trials until the r-th success occur.
7. Poisson Distribution
: An experiment that counts the number of times a particular event occur in a given time or on given physical object (where mean occurring rate is λ). If we set X to be the number of times a particular event occur in the Poisson experiment.
Relationships between Discrete Distributions
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