Two aspects of Galton's problem are considered here—the tendency for cultural diffusion to inflate coefficients of correlation and also its tendency to inflate the number of independent cases for significance tests. Spatial autocorrelation is seen as a generally useful tool for measuring and control ling the influence of diffusion. The Strauss-Orans cluster reduction method reduces spatial autocorrelation in 2 x 2 matrices. In special cases, cluster reduction may eliminate Galton's problem entirely by eliminating spatial autocorrelation of key variables. Wirsing's second order partials reduce in flated correlation coefficients. The Orcutt-James correction reduces inflated sample sizes. Where none of these approaches is useful, Zucker's cluster difference test may be helpful. HRAF plans to apply these methods to its HRAFLIB computer program library.