reviewed at some stage. Some instances—for example where data are lacking—may require that researchers judge whether an assumption is reasonable. Researchers can expand this somewhat to consider what effect a departure from the assumptions might produce. Where more extensive data are available, various types of procedures for statistical model validation are available—e.g. for regression model validation. See also Misuse of statistics Robust statistics Statistical hypothesis testing Statistical theory Notes References Cox D. R. (2006), Principles of Statistical Inference, Cambridge University Press. de Gruijter J., Brus D., Bierkens M., Knotters M. (2006), Sampling for Natural Resource Monitoring, Springer-Verlag. McPherson, G. (1990), Statistics in Scientific Investigation: Its Basis, Application and Interpretation, Springer-Verlag. Statistical theory