Small Sample Size for Test of Training Time by Augmented Reality: An Aeronautical Case

Augmented Reality works for learning (growing tendency) in aeronautical sector demand an evaluation that requires experimental sampling, and this is often an expensive process. Usually, sample size is determined by resources availability constraint, which does not guarantee the level of significance (α) and the margin of error (E) required. This paper introduces a congruent sequence of statistical procedures to determine the estimated work sample size for traineeship in assembly operations. Sample size estimations for an aeronautical case are presented considering various scenarios. A minimum necessary sample size is calculated with statistical rigor via formulation and Operating Characteristic Curves.