Statistical Assumptions

Definition: Analytical approaches and models assume certain characteristics of one’s data (e.g., statistical independence, random samples, normality, equal variance,…). Before running an analysis, thes e assumptions should be checked since their violation can change the results and conclusion of a study. Good practice in open and reproducible science is to report ass umption testing in terms of the assumptions verified and the results of such checks or corrections applied.

Related terms: Null Hypothesis Significance Testing (NHST), Statistical Significance, Statistical Validity, Transparency, Type I error, Type II error, Type M error, Type S error

Reference: Garson (2012); Hahn and Meeker (1993); Hoekstra et al. (2012); Nimon (2012)

Drafted and Reviewed by: Graham Reid, Jamie P. Cockcroft, Sam Parsons, Martin Vasilev, Julia Wolska

We are currently working to link the references directly. For now, the complete reference list can be viewed here.