Factor analysis is a family of mathematical techniques that can be used to represent correlations between intelligence tests in terms of a smaller number of variables known as factors. The purpose is to simplify the correlation matrix by using hypothetical underlying factors to explain the patterns in it. When all correlations in a matrix are positive, as they are in the case of IQ, factor analysis will yield a general factor common to all tests. The general factor of IQ tests is referred to as the "g" factor, and it typically accounts for 40 to 50 percent of the variance in IQ test batteries. The presence of correlations between many widely varying cognitive tests has often been taken as evidence for the existence of "g", but McFarland (2012) showed that such correlations do not provide any more or less support for the existence of "g" than for the existence of multiple factors of intelligence.