# Normal Distribution With Examples

In the previous two articles of this unit we learned Binomial distribution and Poisson Distribution, in this article we will learn Normal distribution.

Normal Distribution

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# Category: Probability

# Normal Distribution With Examples

# Poisson Distribution With Examples

# Binomial Distribution With Examples

# All About Moment Generating Function With Examples

# What is Covariance?

# Variance Formula of Random Variable With Example

# Mathematical Expectation of Random Variables With Examples And Expected Value Formula

# Introduction To Cumulative Distribution Function, Marginal Probability And Joint Density Function

# Distribution Function Of Random Variables

# Random Variable And Its Distribution

In the previous two articles of this unit we learned Binomial distribution and Poisson Distribution, in this article we will learn Normal distribution.

Normal Distribution

Now we will learn Poisson distribution. In the previous article we learn Binomial distribution. So letâ€™s start.

Poisson Distribution

Definition

Let X be a discrete

Binomial Distribution

Before starting our discussion on Binomial Distribution we have to understand what Bernoulli Trials is.

Bernoulli Trials

Trials are called Bernoulli trials if

Moment generating function

In this article we will first learn what a moment generating function (mgf) is and then we will learn how to use

Covariance Definition

Covariance is a measure of association between two random variables. Let X and Y be two random variables. Then the covariance is defined

Variance

One of the important measures of variability of a random variable is variance. Let X is a random variable with probability distribution f(x) and

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:Râ†’R defined by F(X) = P(X â‰¤ 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