What's observed is statistics, not the rule, and the goal of modelling is statistics. Once you have statistics, you don't need to assume the rule, because stati

What's observed is statistics, not the rule, and the goal of modelling is statistics. Once you have statistics, you don't need to assume the rule, because statistics tells you what you want to know - quantitative properties of the process. Also since statistics is quantitative, it can be just computed without interpretation, such quantitative properties don't depend on interpretation, simply because they are computable. Maybe you're confused by assumption that rule is identical to statistics, and thus believe statistics uncomputable merely because the Born rule is uncomputable? The fact is the Born rule allows to miscalculate statistics, because the probabilities are unintuitive, there is a precedent. Amplitudes as quantitative properties are sufficient for calculation of statistics. Ironically classical theory of probabilities works the same way: first it assigns arbitrary weight to outcomes, then divides them by the weight of ensemble (usually >1 contrary to QM) to get statistical coefficients. The weights can be scaled by any constant factor, and the calculation still works.