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Classroom notes

On some confidence intervals for estimating the mean of a skewed population

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Pages 412-421 | Received 24 Jan 2006, Published online: 17 Jul 2007
 

Abstract

A number of methods are available in the literature to measure confidence intervals. Here, confidence intervals for estimating the population mean of a skewed distribution are considered. This note proposes two alternative confidence intervals, namely, Median t and Mad t, which are simple adjustments to the Student's t confidence interval. In order to compare the performance of these intervals, the following criteria are considered: (i) coverage probability; (ii) average width; and (iii) ratio of coverage to width. A simulation study has been undertaken to compare the performance of the intervals. The simulation study shows that for small sample size and moderate to highly skewed distributions, the proposed Median t performs the best in the sense of higher coverage, and the Mad t performs best in the sense of smaller confidence width. The proposed methods are very easy to calculate and are not overly computer-intensive, like Bootstrap confidence intervals. Some real-life examples have been considered that support the findings of the paper to some extent.

Acknowledgement

The authors thank the referee for his valuable comments, which improved the quality and presentation of the paper greatly.

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