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Normal Distribution

In statistics and probability distribution is called normal or Gaussian distribution Gaussian distribution to probability distributions of continuous variable that appears most often approximate real phenomena.

The graph of its density function has a bell shape and is symmetric about a particular statistic. This curve is known as a Gaussian and is a graph of a Gaussian function.

The importance of this distribution is that it allows modeling many natural phenomena, social and psychological. While the mechanisms that underlie much of this phenomenon are unknown, by the enormous amount of uncontrollable variables involved in them , the use of the normal model can be justified by assuming that each observation is obtained as the sum of a few independent causes .

In fact, the statistic is a mathematical model to describe a phenomenon only , without explanation. Causal explanation for the experimental design is necessary, hence the use of statistics in psychology and sociology is known as correlational method.

The normal distribution is also important because of its relation to the least squares estimation, one of the simplest methods of estimation and old.

Some examples of variables associated with natural phenomena follow the normal model are:

• Morphological characteristics of individuals such as height;

• Physiological characteristics as the effect of a drug;

• Sociological character as the consumption of a certain product by the same group of individuals;

• Psychological characteristics such as IQ;

• Noise level in telecommunications;

• Errors made in measuring certain quantities;

etc.

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