Business Excellence, Vol. 7 No. 1, 2013.
Professional paper
USE OF POWER ANALYSIS IN CHOOSING APPROPRIATE SAMPLE SIZE FOR QUALITY INSPECTION
Ksenija Dumičić
orcid.org/0000-0001-7131-9455
; University of Zagreb, Faculty of Economic & Business – Zagreb
Berislav Žmuk
orcid.org/0000-0003-3487-1376
; University of Zagreb, Faculty of Economic & Business – Zagreb
Abstract
Selection of an appropriate sample size is one of the most important aspects of any quality inspection. The right sample size enables making valid conclusions about the quality of the product with minimum necessary resources. The choice of sample size and the probability of Type II error (ß) are closely connected. The purpose of this paper
is to examine how usage of a statistical power analysis can improve researcher’s decision about choosing an appropriate sample size for experimental purposes and quality inspection. Apart from sample size, the power of a study (1- ß) or the probability that the study will yield signifi cant results is determined by the magnitude of the treatment effect and by the level of statistical signifi cance required (α). The goal of power analysis is to balance values of these three factors to get an appropriate power. Impact of individual changes of each factor on the power was observed through a hypothetical statistical example based on a signifi cance test in which the diff erence between proportions of two independent samples was estimated. Power and Precision soft ware was used for calculations. Results of the power analysis have shown that increase in eff ect size, sample size and/or level of statistical signifi cance lead to an increase in power. This means if power increased
and/or eff ect size and/or level of statistical significance decreased, a larger sample size would be required. This paper demonstrates the usefulness of using statistical power analysis in determining
appropriate sample size and warns about possible consequences of erroneously selected sample size.
Keywords
statistical power analysis; sample size; effect size; Type I error; quality inspection; independent samples
Hrčak ID:
106144
URI
Publication date:
30.6.2013.
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