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.

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

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

It includes discrete and continuous random variables, their probability distributions and analytical and statistical methods for determining the mean, variance and higher order moments that ...

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 ...

In a number of situations we are faced with the problem of determining efficient estimates of the mean and variance of a distribution specified by (i) a non-zero probability that the variable assumes ...

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

You can use the RAND () function to establish probability and create a random variable with normal distribution.