Ratio Estimators in Stratified Random Sampling

Abstract

This paper considers some ratio-type estimators and their properties are studied in stratified random sampling. The results are supported by an application with original data.

Hartley-Ross type unbiased estimators using the Stratified Random Sampling

“…In this article, we study on the estimators given by Kadilar and Cingi [5], [6] to obtain the unbiased estimation of the population mean in the stratified random sampling. Both the theoretical and empirical results show that the suggested unbiased estimators have smaller variance values than the compared estimators under the determined conditions.…”

“…Firstly, comparing the variance of the proposed estimators in (2.6) with the MSE of the estimators given in Kadilar and Cingi [5], we have the following inequality…”

Modified Exponential Type Estimator for Population Mean Using Auxiliary Variables in Stratified Random Sampling

“…A number of papers on ratio type estimators appeared based on different type of transformation. Kadilar and Cingi [6] introduced an estimator for the population mean using known value of some population parameters in the SRS given by …”

“…The Journal of Operations Research, Statistics, Econometrics and Management Information Systems ISSN 2148-2225 httt://www.alphanumericjournal.com/ The Population I is taken from [6]. It is concerning the number of teachers as study variable and the number of students as auxiliary variable in both primary and secondary schools for 923 districts at six regions (as 1: Marmara 2: Aegean 3: Mediterranean 4: Central Anatolia 5: Black Sea 6: East and Southeast Anatolia) in Turkey in 2007.…”

“…Diana [5] suggested a class of estimators of the population mean using one auxiliary variable in the stratified random sampling and examined the MSE of the estimators up to the k-th order of approximation. Kadilar and Cingi [6], Singh and Vishwakarma [7,8], Singh et al [9] proposed estimators in stratified random sampling. There are also some recent studies proposing estimators depending on the exponential function.…”