Performance of Some Confidence Intervals for Estimating the Population Coefficient of Variation under both Symmetric and Skewed Distributions

  • Moustafa Omar Ahmed Abu-Shawiesh
  • Hayriye Esra Akyüz
  • BM Golam Kibria
DOI: https://doi.org/10.19139/soic.v7i2.630
Keywords: Augmented-large-sample, Confidence Interval, Coefficient of Variation, Coverage Probability, Average Width.

Abstract

This paper aims to compare the performance of proposed confidence intervals for population coefficient of variation (CV) with the existing confidence intervals, namely, McKay, Miller, and Gulher et al. confidence intervals under both symmetric and skewed distributions. We observed that the proposed augmented-large-sample (AA&K-ALS) confidence interval performed well in terms of coverage probability in all cases. The large-sample (AA&K-LS) and adjusted degrees of freedom (AA&K-ADJ) confidence intervals had much lower coverage probability than the nominal level for skewed distributions. However, the average widths of the AA&K-LS confidence interval are narrower than that of the rest confidence intervals. Two real-life data are analyzed to illustrate the implementation of the several methods.

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Published
2019-05-17
How to Cite
Abu-Shawiesh, M. O. A., Akyüz, H. E., & Kibria, B. G. (2019). Performance of Some Confidence Intervals for Estimating the Population Coefficient of Variation under both Symmetric and Skewed Distributions. Statistics, Optimization & Information Computing, 7(2), 277-290. https://doi.org/10.19139/soic.v7i2.630
Issue
Vol 7 No 2 (2019)
Section
Research Articles
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