Mathematical Expectation of Random Variables
In the last three articles of probability we studied about Random Variables of single and double variables, in this article
In this is article we are going to learn about the terms two dimensional random variable, cumulative distribution function, marginal probability and joint density function.
Distribution Function Definition
Let X be an random variable, then the function such that F:R→R defined by F(X) = P(X ≤ x) is called distribution
Random Variable
By a random variable, we mean a real number x connected with the outcome of a random experiment. Random variables are of two
Bayes’ Theorem
Let B1, B2, B3, …, Bn be n pairwise mutually exclusive and exhaustive set of events connected to a random experiment E where
Conditional Probability
To understand Conditional Probability let us have examples from the real life situations. In the experiment of throwing a dice one might be
