# Probability & Random Processes - Final Exam Review

This page will just contain the most essential equations that pertain to topics on the final exam

## Set Theory

## Table of Discrete Random Variables

Name of Random Variable | Description of variable | PMF Function | Expected Value- | Variance - |
---|---|---|---|---|

Bernoulli | number successes in 1 trial | |||

Geometric | number of trials until 1st success | |||

Binomial | number of successes in n trials | |||

Pascal | number of trials until k successes | |||

Poisson | Probability of x arrivals in T seconds | |||

Discrete Uniform | Probability of any value between k and l |

## Table of Continuous Random Variables

Name | Form | CDF | |||

Uniform | |||||

Exponential | |||||

Erlang | |||||

Gaussian | * |

*****Note that this is the*standard normal*CDF of the Gaussian random variable. To adjust for and use

## List of Essential Equations

#### Expected Value

#### Variance

#### Covariance & Correleational Coefficients

#### Independent Variables

Given two ** independent** random variables: