fundamental for much of statistical inference. Indeed, state this: "The majority of the problems in statistical inference can be considered to be problems related to statistical modeling. They are typically formulated as comparisons of several statistical models." Common criteria for comparing models include the following: R2, Bayes factor, Akaike information criterion, and the likelihood-ratio test together with its generalization, the relative likelihood. See also All models are wrong Blockmodel Conceptual model Design of experiments Deterministic model Effective theory Predictive model Response modeling methodology Scientific model Statistical inference Statistical model specification Statistical model validation Statistical theory Stochastic process Notes References . . . . . . Further reading Davison, A. C. (2008), Statistical Models, Cambridge University Press Freedman, D. A. (2009), Statistical Models, Cambridge University Press Helland, I. S. (2010), Steps Towards a Unified Basis for Scientific Models and Methods, World Scientific Kroese, D. P.; Chan, J. C. C. (2014), Statistical Modeling and Computation, Springer Mathematical modeling Statistical theory