Normal Probability Distribution

The Normal Distribution can be viewed as the limiting distribution of a binomial random variable. That is, in a binomial experiment, if we use a fixed probability of success p, we can analyze what happens as the number of trials n increases. To visualize what happens, we can construct histograms for a fixed p and increasingly large n.

-->

The Below figure is an example of Normal Distribution:

The normal distribution is often used to describe, at least approximately, any variable that tends to cluster around the mean. For example, the heights of adult males in the United States are roughly normally distributed, with a mean of about 70 inches (1.8 m). Most men have a height close to the mean, though a small number of outliers have a height significantly above or below the mean.


-->Importance of Normal Distribution:

• Normal Distribution will appear in the different statistical applications.
• Because Normal Distribution is the central limit theorem and it is used to define the addition of random variables and their approximately distributed in normally and the number of observation is large.
• Suppose if the distribution is not exactly normal, it is convenient to assume as a normal distribution. It is a good approximation.