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.

Fundamental notions such as random variables, distribution functions and probability density functions facilitate the analysis of both discrete and continuous outcomes.

A discrete distribution is a statistical probability distribution that represents the possible discrete values a variable can take.

Description Probability, statistics, reliability and decision with applications in engineering. Probability of events, discrete and continuous random variables, probability density functions and ...

The problem considered here is the estimation of the probability density function f (x1, ⋯, xp) at a point z = (z1, ⋯, zp) where f is positive and continuous. An estimator is proposed and consistency ...

Previously suggested methods for constructing confidence bands for cumulative distribution functions have been based on the classical Kolmogorov-Smirnov test for an empirical distribution function.

Key Takeaways Expected value describes the long-term average level of a random variable based on its probability distribution.