the inflated negative

binomial distribution has three parameters).

The range of probabilities of negative

binomial distribution is obtained using the following calculation (JOHNSON and KOTZ, 1969):

Physical conditions: We get

Binomial distribution under the following conditions

In the MT model, a pure

binomial distribution cannot be assumed because the total number of states is greater than 2; however, a similar variance structure can be achieved by treating each of the transitions as a separate

binomial distribution and summing the variances together.

In this section, we proposed a new method for odds ratio estimation using Empirical Bayes method in two independent

binomial distributions.

The response here is the frequency of women availing themselves of ANC, which is normally assumed to follow the Poisson distribution or negative

binomial distribution.

We fit the transmission data from patients within subgroups to the negative

binomial distribution with mean R and dispersion parameter k, which characterizes individual variation in transmission, including the likelihood of superspreading events (i.

M], the number of portfolio defaults, n, has a

binomial distribution,

The main contention of this paper relies on detecting the existence of skill with the generalized

binomial distribution, using an established analogy with winning in sports.

Using Monte Carlo simulation techniques, the zero-inflated binomial samples were generated while taking into account the ZIB model (RUCKSTUHL; WELSH, 2001), characterized by the mixture of two components in such a way that one component presumes that the occurrence of zero is defined by a [gamma] probability, while the other component represents a

binomial distribution with a (1-[gamma]) probability.

Measurement of distributional aggregation of species Following a previous study (Chen 2013a) instead of using the negative

binomial distribution26) The

binomial distribution is universally accepted by statisticians and is commonly used in science and industry for predicting events such as the number of patients who will have an adverse reaction to a drug or the probability of a sports team winning a series of games.

The

binomial distribution is a discrete probability distribution arising when the probability of success (p) in each of a fixed or known number of Bernoulli trials (n)is either unknown or random.

The weights present a

binomial distribution with the random parameter (2[[beta].

Moreover, of all the 15 sampling events performed, ten samples adjusted to the negative

binomial distribution model with non-significant chi-square value.