Abstract
This chapter develops statistical inference for population mean and total using stratified ranked set sample (SRSS). A stratified simple random sample (SSRS) selects a simple random sample (SRS) from each stratum population. The SRSS design, unlike SSRS, creates a ranked set sample having ranking structure from each stratum populations to form a stratified sample. Hence, in addition to stratum structure, it induces an additional ranking structure within stratum samples. SRSS is constructed from a finite population using a without replacement sampling design. Inference is constructed under both randomized design and a super population model. In both approaches, this chapter shows that the estimators of population mean and total are unbiased. The chapter also constructs unbiased estimators for the variance of sample mean and develops confidence and prediction intervals for the population mean. The empirical evidence shows that the proposed estimator perform better than its competitors in the literature. The proposed estimator is applied to apple production data in a finite population setting.
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