TY - JOUR AU - Moustafa Omar Ahmed Abu-Shawiesh AU - Hayriye Esra Akyüz AU - BM Golam Kibria PY - 2019/05/17 Y2 - 2024/03/29 TI - Performance of Some Confidence Intervals for Estimating the Population Coefficient of Variation under both Symmetric and Skewed Distributions JF - Statistics, Optimization & Information Computing JA - Stat., optim. inf. comput. VL - 7 IS - 2 SE - Research Articles DO - 10.19139/soic.v7i2.630 UR - http://www.iapress.org/index.php/soic/article/view/soic.190602 AB - 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. ER -