Nurdan YENİAY KOÇER, Yaprak Arzu ÖZDEMİR, Fikri GÖKPINAR

New Bootstrap Methods for the Hypothesis Tests of the Population Mean in Ranked Set Sampling

Ranked Set Sampling is an efficient technique when it is difficult to measure sampling units in respect to cost or time. Although this technique can be used for every sample sizes, the small sample sizes are preferred for better ranking. However, when the sample sizes are small, it is very difficult to obtaindistribution of the statistic for the statistical inference such as hypothesis test. In this case, resampling techniques like bootstrap can be used to construct pseudo distribution of the statistics. In this study, the bootstrap methods for hypothesis test about population mean under ranked set sampling is given. A simulation study is also performed to examine the performance of these methods.

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