Factor analysis is the denomination attributed to the multivariate parametric statistical techniques used to study the inter- relationship between a set of observed variables. It is a process essentially intended to reduce and summarize data, thus becoming a good option for a better management of real information, generating remainder variables that are more significant and easier to work with, in various fields of scientific research. However, a possible limitation of factor analysis is that there are no conclusive statistical tests regularly employed in testing the hypotheses. Consequently, it is difficult to know if the results are merely accidents, or indeed, reflect something of significance. For this reason, this study intends to establish an inferential procedure for factor analysis, using CIS (Computer Intensive Statistics) techniques, such as the bootstrap and jackknife, which allow factor analysis to pass out of the purely descriptive, solving the problem of the insufficiency of sample distribution theory as seen in multivariate techniques.