global-journal-of-science-frontier-research-f-mathematics-decision Global Journal of Science Frontier Research - F: Mathematics & Decision 0975-5896 2249-4626 Global Journals Publishing Group Incorporated 75237 A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling SanaullahAamir PAKISTAN, GC University, Lahore, Pakistan. 20 11 2012 12 F14 33 45

In this paper a class of improved estimators has been proposed for estimating population mean in two phase (double) sampling when only partial information is available on either of two auxiliary variables. Under simple random sampling (SRWOR), expressions of mean square error and bias have been derived to make comparison of suggested class with wide range of other estimators. Empirical study has also been given using five different natural populations. Empirical study confirmed that the suggested class of improved estimators is more efficient under percent relative efficiency (PRE) criterion.

 double sampling auxiliary variable partial information bias mean square error. Full Text

In this paper a class of improved estimators has been proposed for estimating population mean in two phase (double) sampling when only partial information is available on either of two auxiliary variables. Under simple random sampling (SRWOR), expressions of mean square error and bias have been derived to make comparison of suggested class with wide range of other estimators. Empirical study has also been given using five different natural populations. Empirical study confirmed that the suggested class of improved estimators is more efficient under percent relative efficiency (PRE) criterion.