One-sided confidence intervals for population variances of skewed distributions

In this article we study the coverage accuracy of one-sided bootstrap-t confidence intervals for the population variances combined with Hall's and Johnson's transformation. We compare the coverage accuracy of all suggested intervals and intervals based on the Chi-square statistic for variances of positively skewed distributions. In addition, we describe and discuss an application of the presented methods for measuring and analyzing revenue variability within the food retail industry. The results show that both Hall's transformation and Johnson's transformation approaches yield good coverage accuracy of the lower endpoint confidence intervals, better than method based on the Chi-square statistic. For the upper endpoint confidence intervals Hall's bootstrap-t method yields the best coverage accuracy when compared with other methods.