The process of transforming statistical data, such as some sort of measurements, into that usually combine a number of independent is called factor analysis. The techniques for determining or estimating various parameters in such algebraic or the values of the variables therein are also included in the definition of this term. Many techniques for performing factor exist. Because they are the most likely to provide direct numerical results, the most accepted by mathematical theoreticians require laborious computations to be carried out. For centuries, as mathematics developed, this fact limited the accuracy and amount of analysis that any particular mathematician was able or willing to attempt. But with the advent of sophisticated and computers, such computations are much easier and faster to perform with greater accuracy than ever before, allowing factor analysis to be completed much more quickly even with extremely complex equations.

The goal of factor analysis is to account for a set of observed results in terms of variables in the least complicated equation or set of equations possible. In addition, an attempt is made to identify within the equation(s) that are common to or independent of other factors. If one type of factor has an influence on all of another type, it is known as a general factor, if only on some of the other type, it is called a group factor. A common factor with both positive and negative effects on others is called bipolar. Identification of the types and values of factors is vital to factor analysis.