Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that neither means, variances, nor monotonicity of distances between ordered pairs of scores will affect the results, by factor analyzing a matrix of Spearman's rho coefficients. Since Spearman's rho is a scale-free non-parametric procedure, the benefits of non-parametric statistics can be applied to this application. An example of six variables and seven cases demonstrates regular factor analysis using Pearson's "r" for the correlation matrix and non-parametric factor analysis using Spearman's rho for the correlation matrix. Advantages of the non-parametric strategy are discussed. Three tables contain analysis data, the correlation matrix, and the varimax rotated factor matrix. (SLD)