Abstract
The single-sided lower tolerance factors frequently used for non-trending assessment of the validation bias and bias uncertainty are sensitive to departures from normality. When used properly, the tolerance limits ensure that an appropriate fraction of the true population of applicable critical experiments lies above the calculated lower tolerance limit with the required statistical confidence level. One condition necessary to ensure that the appropriate proportion of the true population of keff values in the validation suite lies above the lower tolerance limit is that the assumption that the normality of the underlying population of critical experiments is valid or conservative.
This paper discusses various methods used to assess whether the assumption that the validation suite may be treated as a random sample drawn from a normal distribution is acceptable. Techniques for assessing the validity of this underlying assumption include common omnibus hypothesis tests for normality, assessment of sample skewness and kurtosis of the validation suite, and graphical techniques. These techniques are used to assess the nature and potential conservatism/nonconservatism imparted by various departures from normality where possible. A review of hypothesis testing is also presented to frame the discussion of omnibus normality tests. Additionally, two cases are analysed with these techniques to provide an example of how they should be implemented.
