## Normal Probability Distributions

Normal Probability Distributions Intro:

Definition of Normal Distribution Probability Function:

The concept “probability of X=x” is replaced by the “probability density function fx( ) evaluated at X=x”

A picture of this function with X=x plotted on the horizontal and fx( ) evaluated at X=x” plotted on the vertical is the familiar bell-shaped (“Gaussian”) curve.

In mathematical statistics it is frequently necessary to deal with hypothetical distribution functions. The fundamental materials with which a statistician operates are numbers.

The development of statistics has involved everything into it. From stock market to clairvoyant testing, from rolling of a dice to growth percentile chart nothing can go without statistics. What actually does statistics do? Well, in simple words we can say it just provides a mathematical platform to present experimental data. Not to mention observational data.

In this article. I will discuss different types of averages and why averages becomes an import.

In this article I will discuss, how to get the area under a curve without integration with approximation methods like Simpson rule and Trapezodial Rule.

This article will discuss the importance of normal distribution in statistical test process and the methods to test normal distribution for any data set whether it is small or large sample size.