# Normal Distribution

## This article shall help the reader understand the concept of Normal Distribution and its implication on various aspects of analysis.

This article shall help the reader understand the concept of Normal Distribution and its implication on various aspects of analysis.

Normal Distribution

Normal distribution is a type of continuous probability distribution. This concept is mainly applicable to continuous data only except few distributions in discrete data such as Binomial and Poisson distribution, which also follows normal distribution.

The entire business world is full of uncertainties. You don’t know how many products will be sold next month, you don’t know how much will be the demand of your product in the market next month, you don’t know how many units of product you will be able to manufacture next month. Uncertainties regarding these facts haunt even the best business planners in the world. So, all business planners, in order to make rational decision, want to have numerical values of such uncertainty. Probability can be best understood as numerical value of uncertainty and Probability distributions can be understood as such distribution where we can find the probability of outcome. We can predict with certain precision the probability that we will get certain random variable.

Normal distribution is also a type of probability distribution where we can easily assign numerical value for the uncertainty of certain event. The concept of normal distribution was developed by Carl Frederic Gauss, a German mathematician. He conceptualized normal distribution, where the distribution Curve exhibited following characteristics. • Unimodal (One peak / Single Mode) • Mean, Median and Mode will be equal • Mean Divides the bell curve symmetrically (mirror image division) • Tails of the curve never touches X- axis. The last characteristic (Tails never touches X- Axis) of normal distribution is probability the only limitation that the normal distribution has. Because of this limitation, normal curve will never represent 100% of the process.

Normal Distribution

Normal distribution becomes imperative in our business planning because of its Empirical Law. Empirical law is a law that helps us plans future performance of business. According to this law, if our data is normally distributed and if the Mean and the standard deviation of the distribution are known, then we can predict our distribution.

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