A modified robust confidence interval for the population mean of distribution based on deciles
Author:
Abu-Shawiesh Moustafa Omar Ahmed1ORCID, Sinsomboonthong Juthaphorn2ORCID, Kibria Bhuiyan Mohammad Golam3ORCID
Affiliation:
1. Department of Mathematics, Faculty of Science , The Hashemite University , P. O. Box 330127 , Zarqa , Jordan . 2. Department of Statistics, Faculty of Science , Kasetsart University , Bangkok , Thailand . 3. Department of Mathematics and Statistics , Florida International University, University Park , Miami FL 33199, USA .
Abstract
Abstract
The confidence interval is an important statistical estimator of population location and dispersion parameters. The paper considers a robust modified confidence interval, which is an adjustment of the Student’s t confidence interval based on the decile mean and decile standard deviation for estimating the population mean of a skewed distribution. The efficiency of the proposed interval estimator is evaluated on the basis of an extensive Monte Carlo simulation study. The coverage ratio and average width of the proposed confidence interval are compared with certain existing and widely used confidence intervals. The simulation results show that, in general, the proposed interval estimator’s performance is highly effective. For illustrative purposes, three real-life data sets are analyzed, which, to a certain extent, support the findings obtained from the simulation study. Thus, we recommend that practitioners use the robust modified confidence interval for estimating the population mean when the data are generated by a normal or skewed distribution.
Publisher
Polskie Towarzystwo Statystyczne
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Reference35 articles.
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