Often quantitative data analysis begins with an inspection of attribute variable histograms. Ratio scale demographic variables, such as population density (which has a natural, meaningful absolute 0 value), are expected to conform, at least approximately, to a normal probability distribution. Frequently this conformity requires that these variables be subjected to a symmetricizing, variance stabilizing transformation, such as the Box-Cox class of power functions or the Manley exponential function. Counts (i.e., aggregated nominal measurement scale) data used to construct ratios, such as the crude fertility rate (i.e., number of births per number of women in the child bearing age cohort), are expected to conform to a Poisson probability distribution. And, counts data that constitute some subset of a total, such as the percentage of people at least 100 years of age or the percentage of a population that is the women in the child bearing age cohort, are expected to conform to a binomial probability distribution.