MMP.13:4.1 - Fix the target before choosing a fitting routine

Write q=g(theta), where theta denotes the unknowns in the observation model. It can index a distribution or unknown function, not just a finite vector. State the population, conditions and time range that make q meaningful. Distinguish unknowns needed only to explain the records from the target being returned.

For prediction, instead name the new outcome Y_new and its observing conditions. A conditional mean of Y_new is a function of theta; the realized Y_new also varies under the model. A proposed intervention requires a supplied causal identification argument before a fitted association can be interpreted as its effect.

Select the smallest result that changes the next use. It may be a point estimate with a stated error property, an upper confidence bound, a posterior probability of a threshold, or a predictive distribution. A threshold action still needs its loss or decision rule; a probability or confidence level does not choose that action by itself.