So far we have looked at discrete random variables and how to calculate/visualize their distribution functions. In this lesson, we shall deal with continuous variables and probability density function ...

So far, you learned about discrete random variables and how to calculate or visualize their distribution functions. In this lesson, you'll learn about continuous variables and probability density ...

The joint probability density function \(f\) of two random variables \(X\) and \(Y\) satisfies, for every \(a_1 b_1\) and \(a_2 b_2\), \[ P(a_1\le X\le b_1, a_2\le Y ...

Abstract: Here we discuss optimization over infinite‐dimensional vector spaces. The most simple case is when the variable is a real‐valued function of a real variable. This has applications in optimal ...