Understanding continuous random variables is essential in statistics, as they form the foundation for modelling and analysing real-world data that varies smoothly rather than in steps. Use this page ...

This table represents a discrete probability function, which shows the probability associated with each possible value of a discrete random variable. Such distributions can also be displayed ...

A probability density function, also known as a bell curve, is a fundamental statistics concept, that describes the likelihood of a continuous random variable taking on a specific value.

Why would faker couldn't generate number base on some probability of that number to be generated? Btw, I'm no mathematician, so I might be incorrect with what I explain, but I still think faker could ...

Kernel density estimation (KDE) is a non-parametric method to estimate the probability density function of a random variable by taking the summation of kernel functions centered on each data point.

In this work, we propose a novel procedure for deriving a discrete counterpart to a continuous probability distribution. This procedure or, better, this class of procedures, is based on an appropriate ...

Fusing probabilistic information is a fundamental task in signal and data processing with relevance to many fields of technology and science. In this work, we investigate the fusion of multiple ...