Most statistical approaches to outlier detection are based on building a probability distribution model and considering how likely objects are under that model.
Probalistic Definition of an Outlier: An outlier is an object that has a low probability with respect to a probability distribution model of the data.
The Gaussian(nomal) distribution is one of the most frequently used distributions in statistics. There is little chance that an object(value) from a N(0,1) distribution
will occur in the tails of the distribution. For instance, there is only a probability of 0.0027 that an object lies beyond the central area between -3 and +3 standard
deviations.