Probability Distributions in R

In statistics, the Kullback–Leibler (KL) divergence is a distance metric that quantifies the difference between two probability distributions. If we have two…

In statistics, two variables follow a bivariate normal distribution if they have a normal distribution when added together. This tutorial explains how…

This tutorial explains how to work with the Chi-Square distribution in R using the following functions: dchisq: returns the value of the…

The central limit theorem states that the sampling distribution of a sample mean is approximately normal if the sample size is large…

The triangular distribution is a continuous probability distribution with a probability density function shaped like a triangle. It is defined by three…

The multinomial distribution describes the probability of obtaining a specific number of counts for k different outcomes, when each outcome has a…

You can use the following methods to work with the normal CDF (cumulative distribution function) in R: Method 1: Calculate Normal CDF…

The Empirical Rule, sometimes called the 68-95-99.7 rule, states that for a given dataset with a normal distribution: 68% of data values fall within…

In statistics, the gamma distribution is often used to model probabilities related to waiting times. We can use the following functions to…

You can use the following basic syntax to calculate and plot a cumulative distribution function (CDF) in R: #calculate empirical CDF of…