Normal or gaussian distribution

Normal distribution also known as gaussian distribution was Discovered by Carl Friedrich Gauss.

It is the most important probability distribution in statistics because it fits many natural phenomena such as heights, blood pressure, measurement error, and IQ scores which follow the normal distribution.

It is a probability distribution that is symmetric about the mean

Mean = median = mode

Symmetric around center

Forms bell shaped curve and are under curve =1

Consider a variable x which belongs to normal/gaussian distribution with mean, variance and standard distribution given below,

Then Its values must be symmetrical around the center. Which means 50% of value must be to the left of center and remaining 50 to the right.

In terms of mean and standard deviation normal distribution can be represented as

A variable following a normal distribution must satisfy following three formulae,

That’s all about normal/ gaussian distribution. Hope this blog is useful.