Small Sample Design Allowables from Paired Data Sets
ARMY LAB COMMAND WATERTOWN MA MATERIAL TECHNOLOGY LAB
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This paper identifies an acceptable statistical procedure for obtaining design allowable values from a small set of material strength data. The allowable represents a material design number defined as the 95 lower confidence bound on the specified percentile of the population of material strength data. The percentiles are the first and tenth for the A and B allowables. The proposed method reduces the penalties commonly associated with small sample allowable computation by accurately maintaining the definition requirements and reducing variability in the estimate. Application of very small samples will obviously reduce costs in testing and manufacturing which is the primary motivation for this study. In the evaluation process five methods were considered for computing the design allowable. Three of these methods involved certain statistical distribution assumptions while the other two were nonparametric procedures. The latter methods introduced a pooling process such that the small sample was combined with a larger, previously obtained sample. Monte Carlo studies showed that the nonparametric procedures are the most desirable for computing the design allowable value.
- Statistics and Probability