 A second problem for the statistical approach is whether it can account not only for our preference for small numbers over large numbers (when it comes to picking values for coefficients or exponents in model equations), but also our preference for whole numbers and simple fractions over other values. In Gregor Mendel’s original experiments on the hybridization of garden peas, he crossed pea varieties with different specific traits, such as tall versus short or green seeds versus yellow seeds, and then self-pollinated the hybrids for one or more  generations.[18]  In each case one trait was present in all the first-generation hybrids, but both traits were present in subsequent generations. Across his experiments with seven different such traits, the ratio of dominant trait to recessive trait averaged 2.98 : 1. On this basis, Mendel hypothesized that the true ratio is 3 : 1. This ‘rounding’ was made prior to the formulation of any explanatory model, hence it cannot have been driven by any theory-specific consideration. This raises two related questions. First, in what sense is the 3 : 1 ratio hypothesis simpler than the 2.98 : 1 ratio hypothesis? Second, can this choice be justified within the framework of the statistical approach to simplicity? The more general worry lying behind these questions is whether the statistical approach, in defining simplicity in terms of number of adjustable parameters, is replacing the broad issue of simplicity with a more narrowly—and perhaps arbitrarily—defined set of issues.