Normalization

  1. The mathematical process of transforming a data set into a Gaussian (“normal”) distribution, so that standard statistical concepts (e.g, mean, median, variance, kurtosis) are valid. Unless the data have been verified as conforming or transforming into the Gaussian shape, no parametric statistics should be trusted. Note that this verification process “consumes” degrees of freedom in the data, which means that extra test runs, for example, must be dedicated to this purpose.
  2. The database design process of grouping atomic data items into sets such that the elements within each set exist in 1:1:…:1:1 relation (see Relational Table Criteria). The abstract composition of each set is equivalently termed a “tuple” or “relation”. The later term is the conceptual root of a “relational database”. A practical application of Set Theory, normalization is mathematically assured to maximize “data integrity” by absolutely minimizing the number of opportunities for incorrect data entry.