Abstract: This paper considers the construction of bootstrap confidence intervals for estimating finite population quantiles. The intervals involve estimators which make use of the auxiliary information provided by an available auxiliary variable. The proposed bootstrap confidence intervals are validated under theoretical (asymptotic) and empirical points of view, indeed simulations with natural populations are carried out in order to compare the behavior of the proposed intervals with the obtained from standard normal approximations.
Abstract: The objective of the present study is to estimate the difference between two population means when some observations on the first and second characteristics are missing form the sample. The proposed estimator defined for general sampling design is computationally simple and an easy expression for its variance is obtained. The proposed estimator is applied to two years data concerning the commercial operations in Andalucia.
Keywords: Auxiliary information, missing data, Horvitz-Thompson estimator, simple random sampling