Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn to assess risk and potential gains.

Probability distributions are fundamental tools in statistics and probability theory, offering a mathematical framework to describe the likelihood of different outcomes in a random experiment or ...

The total area under the curve must equal 1, representing the fact that the probability of some outcome occurring within the entire range is certain. \[\int_{-\infty}^{\infty}f\left(x\right)dx=1\] ...

A discrete random variable is a type of random variable that can take on a countable set of distinct values. Common examples include the number of children in a family, the outcome of rolling a die, ...

Abstract: This article proposes an approximated Bayesian entropy estimator for a discrete random variable. An entropy estimator that achieves least square error is ...

Abstract: We discuss properties of the “beamsplitter addition” operation, which provides a non-standard scaled convolution of random variables supported on the non-negative integers. We give a simple ...

Roll a die and ask students to identify the random variable. Since a die can only take on values of 1, 2, 3, 4, 5, or 6, this is a discrete random variable. Repeat ...

A random variable is a mathematical function that maps outcomes of random experiments to numbers. It can be thought of as the numeric result of operating a non-deterministic mechanism or performing a ...