PROBABILITY DISTRIBUTIONS IN R

A statistical distribution, also known as a probability distribution, is a mathematical function that describes the likelihood of different outcomes or values occurring in a dataset or a random phenomenon

CONTINUOUS DISTRIBUTIONS

Continuous distributions describe the probability distribution of a continuous random variable. This type of random variable can take on any value within a specified range or interval, and the probability of obtaining any specific value is zero

Create and plot Normal distributions in R

Normal distribution

dnorm() pnorm() qnorm() rnorm()

Use the dunif, punif, qunif and runif functions of the uniform distribution in R

Continuous uniform distribution

dunif() punif() qunif() runif()

Learn how to use the dexp, pexp, qexp and rexp functions of the exponential distribution in R

Exponential distribution

dexp() pexp() qexp() rexp()

DISCRETE DISTRIBUTIONS

Discrete distributions describe the probability distribution of a discrete random variable. This type of random variable can take on only distinct, separate values, typically integers, and the probability associated with each value is defined individually

Binomial distribution in R with the dbinom, pbinom, qbinom and rbinom functions

Binomial distribution

dbinom() pbinom() qbinom() rbinom()

Poisson distribution in R with the dpois, ppois, qpois and rpois functions

Poisson distribution

dpois() ppois() qpois() rpois()

Try adjusting your search query

👉 If you haven’t found what you’re looking for, consider clicking the checkbox to activate the extended search on R CHARTS for additional graphs tutorials, try searching a synonym of your query if possible (e.g., ‘bar plot’ -> ‘bar chart’), search for a more generic query or if you are searching for a specific function activate the functions search or use the functions search bar.