Journal ArticleDOI
One and two sample confidence intervals for estimating the mean of skewed populations: an empirical comparative study
Ayman Baklizi,B. M. Golam Kibria +1 more
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In this paper, the authors consider and propose some confidence intervals for estimating the mean or difference of means of skewed populations, and extend the median t interval to the two sample problem, and suggest using the bootstrap to find the critical points for use in the calculation of median t intervals.Abstract:
In this paper we consider and propose some confidence intervals for estimating the mean or difference of means of skewed populations. We extend the median t interval to the two sample problem. Further, we suggest using the bootstrap to find the critical points for use in the calculation of median t intervals. A simulation study has been made to compare the performance of the intervals and a real life example has been considered to illustrate the application of the methods.read more
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Journal ArticleDOI
Estimating the Population Coefficient of Variation by Confidence Intervals
Shipra Banik,B. M. Golam Kibria +1 more
TL;DR: An attempt has been made to review some existing estimators along with some proposed methods and compare them under the same simulation condition and recommend some possible good interval estimators for the practitioners.
Journal ArticleDOI
Comparison of Some Parametric and Nonparametric Type One Sample Confidence Intervals for Estimating the Mean of a Positively Skewed Distribution
Shipra Banik,B. M. Golam Kibria +1 more
TL;DR: More choices are provided for the practitioners to use best possible interval estimators among many that have been used by several researchers at different times and situations to provide more choices.
Journal ArticleDOI
Confidence Interval for the Mean of a Contaminated Normal Distribution
Journal Article
A simulation study on some confidence intervals for the population standard deviation
TL;DR: In this article, a robust estimator against outliers along with some other existing interval estimators are considered for estimating the population standard deviation, specifically in the presence of outliers and/or data are from a skewed distribution.
Journal ArticleDOI
Parametric and nonparametric confidence intervals for estimating the difference of means of two skewed populations
B. M. Golam Kibria,Shipra Banik +1 more
TL;DR: In this paper, the authors reviewed and proposed several interval estimators for estimating the difference of means of two skewed populations, including the ordinary-t, two versions proposed by Welch [17] and Satterthwaite [15], three versions of Zhou and Dinh [18], Johnson [9], Hall [8], empirical likelihood (EL), bootstrap version of EL, median t, and median t proposed by Baklizi and Kibria [2].
References
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Journal ArticleDOI
Empirical Likelihood Ratio Confidence Regions
TL;DR: In this article, an empirical likelihood ratio function is defined and used to obtain confidence regions for vector valued statistical functionals, and an effective method is presented for computing empirical profile likelihoods for the mean of a vector random variable.
Journal ArticleDOI
Modified t Tests and Confidence Intervals for Asymmetrical Populations
TL;DR: In this paper, a procedure that reduces the effect of population skewness on the distribution of the t variable so that tests about the mean can be more correctly computed is proposed.
Journal ArticleDOI
On the Removal of Skewness by Transformation
TL;DR: In this article, empirical transformations for removing most of the skewness of an asymmetric statistic were proposed, which can be used as the basis for accurate confidence procedures or hypothesis tests and can be employed in conjunction with either a normal approximation or the bootstrap.
Journal ArticleDOI
Edgeworth corrected pivotal statistics and the bootstrap
Lavy Abramovitch,Kesar Singh +1 more
TL;DR: In this paper, a general procedure for multistage modification of pivotal statistics is developed to improve the normal approximation, and explicit formulae are given for some basic cases involving independent random samples and samples drawn without replacement.
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