Continuous random variables can take any value within a range. Unlike discrete variables, they include fractional and decimal values. These variables are often modeled using probability distributions.

Continuous Variable: can take on any value between two specified values. Obtained by measuring. Discrete Variable: not continuous variable (cannot take on any value between two specified values).

The binomial distribution models the number of successes in a fixed number of independent Bernoulli trials, each with the same probability of success. The chi-square distribution is often used in ...

A complete visual laboratory for continuous probability distributions using Python. This project helps you understand and explore continuous random variables visually.

Chance and uncertainty play a role in many aspects of life. A solid understanding of probability enhances critical thinking and empowers us to make well-informed decisions in everyday situations such ...

The University of Texas at Dallas, Richardson, USA. The standard two parameter Beta Distribution is the most widely used distribution for situations wherein a continuous random variable is confined to ...

The ratio R of two random quantities is frequently encountered in probability and statistics. But while for unidimensional statistical variables the distribution of R can be computed relatively easily ...