A likelihood ratio test is given for distinguishing skewness from commingled distributions, using a power transform to remove skewness appropriately for each of the alternatives tested. The alternative hypotheses postulate that the transformed data are from one normal or a mixture of two or three normal homoscedastic distributions. Since each mixture has unique asymmetry, skewness is estimated simultaneously with the means, proportions and variance of components. Commingling cannot be rigorously proven in this way, as some other transform may provide a better approximation to normality. However, the error of asserting admixture whenever there is skewness has been avoided, and estimates of admixture parameters provide a basis for more conclusive tests in relatives or other populations. Two examples are given, one in which adjustment for skeweness left evidence of commingling.

A general linear model is presented here for biological and cultural inheritance involving ten parameters to be estimated from 16 correlations in nuclear families, providing ample degrees of freedom to test goodness of fit. Applied to six lipoprotein traits the model fits acceptably to all, although there is evidence of transient maternal effects for cholesterol and lipemia. Genetic heritability in children ranges from 0.175 for triglyceride to 0.562 for total cholesterol. Cultural heritability in children ranges from 0.012 for VLDL to 0.149 for HDL-cholesterol.

Assuming a perfect correspondence between the site of crossing-over and an observed chiasma, data on meiosis in the human male are used to estimate a mapping parameter which on average turns out to be intermediate between the Kosambi and Carter-Falconer values, but smaller for acrocentrics. A table is given for converting recombination frequencies to map distances.

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