A random variable is one whose value is unknown or a function that assigns values to each of an experiment’s outcomes. A random variable can be discrete or continuous.

Since f (x,y) is a probability distribution, it must sum to 1. Adding probabilities across the rows you get the probability distribution of random variable X (called the marginal distribution of X).

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

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

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 ...

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 ...

Wassily Hoeffding, Probability Inequalities for Sums of Bounded Random Variables, Journal of the American Statistical Association, Vol. 58, No. 301 (Mar., 1963), pp. 13-30 ...