negative binomial distribution rstudio

The negative binomial distribution is a probability distribution used to model the number of successes before a specified number of failures in a sequence of independent and identically distributed Bernoulli trials. In RStudio, you can calculate the negative binomial distribution using the dnbinom(), pnbinom(), qnbinom(), and rnbinom() functions.

1. dnbinom(x, size, prob): This function calculates the probability density function (PDF) of the negative binomial distribution. The parameter x represents the number of successes, size represents the number of failures until the experiment is stopped, and prob represents the probability of success in each trial.

2. pnbinom(q, size, prob): This function calculates the cumulative distribution function (CDF) of the negative binomial distribution. The parameter q represents the number of successes, size represents the number of failures until the experiment is stopped, and prob represents the probability of success in each trial. The CDF gives the probability of obtaining q or fewer successes.

3. qnbinom(p, size, prob): This function calculates the quantile function of the negative binomial distribution. The parameter p represents the probability of obtaining q or fewer successes, size represents the number of failures until the experiment is stopped, and prob represents the probability of success in each trial. The quantile function gives the number of successes corresponding to a given probability.

4. rnbinom(n, size, prob): This function generates random numbers from the negative binomial distribution. The parameter n represents the number of random numbers to generate, size represents the number of failures until the experiment is stopped, and prob represents the probability of success in each trial.

These functions can be used to perform various calculations and analyses related to the negative binomial distribution in RStudio.