The normal distribution is one of the most important probability distributions in statistics in that many statistical analyses build on the assumption that the data follow the normal distribution, and in that many physical and biological phenomena in real life can be approximated by the normal distribution.

A normal distribution is specified by two parameters: mean µ and standard deviation σ. If a random variable X follows the normal distribution with mean µ and standard deviation σ, it is often denoted by XN (µ, σ2). The normal distribution has a bell shape as shown below, which is called the normal curve.

Technically, the normal curve is given by the following formula:


The variable x takes any real value. The mean µ specifies the central location of ...

  • Loading...
locked icon

Sign in to access this content

Get a 30 day FREE TRIAL

  • Watch videos from a variety of sources bringing classroom topics to life
  • Read modern, diverse business cases
  • Explore hundreds of books and reference titles