Sample size estimation for statistical comparative test of training by using augmented reality via theoretical formula and OCC graphs: Aeronautical case of a component assemblage

Abstract

Advances in Augmented Reality applied to learning the assembly operation in terms of productivity, must certainly be evaluated. We propose a congruent sequence of statistical procedures that will lead to determine the estimated work sample size (n̂) according to the level of significance required by the aeronautical sector or a justified similar one and the estimated (sometimes preconceived) value of the plus-minus error (E or E±). We used the Kolmogorov-Smirnov test to verify that a normal distribution fits, it is a nonparametric one (free-distribution). And by taking into account normal population, confidence interval is determined using the Student's t distribution for (n-1) degrees of freedom. We have gotten E error and obtained various sample sizes via statistical formula. Additionally, we proceeded to utilize both an alpha α significance level and a beta β power of the test selected for the aeronautical segment to estimate the size of the sample via application of Operating Characteristic Curves (CCO), being this one of the ways with statistical high rigor. Several scenarios with different n̂ values make up the outcome, herein. We disclosed diverse options for the different manners of estimation. © 2011 Springer-Verlag.