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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Statistical assumptions are general assumptions about statistical populations. Statistics, like all mathematical disciplines, does not generate valid conclusions from nothing. In order to generate interesting conclusions about real statistical populations, it is usually required to make some background assumptions. These must be made with care, because inappropriate assumptions can generate wildly inaccurate conclusions.Given that the validity of conclusions drawn from a statistical analysis depend on the validity of any assumptions made, it is clearly important that these assumptions should be reviewed at some stage. In some instances, for example where data are lacking, this may have to be restricted to just making a judgement about whether an assumption is reasonable. This can be expended slightly to trying to judge what effect a departure from the assumptions might have. Where more extensive data are available, various types of procedure for statistical model validation are available, in particular for regression model validation.