New Product-Type Estimators for the Population Mean Using Quartiles of the Auxiliary Variable

In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.





References:
[1] Cochran, W.G. (1977). Sampling Technique. 3rd edition, Wiley and
Sons. New York.
[2] Jemain, A. A. and Al-Omari, A. I. (2006). Multistage median ranked set
samples for estimating the population mean, Pakistan Journal of
Statistics, 22(3): 195-207.
[3] McIntyre, G. A. (1952). A method for unbiased selective sampling using
ranked sets, Australian Journal of Agricultural Research. 3: 385-390.
[4] Muttlak, H. A., (1997). Median ranked set sampling, Journal of Applied
Statistical Sciences. 6(4): 245-255.
[5] Pandey, B.N. and Dubey, V. (1998). Modified product estimator using
coefficient of variation of auxiliary variable, Assam Statistical Rev.,
2(2): 64-66.
[6] Samawi. H. M. and Muttlak, H. A. (1996). Estimation of ratio using rank
set sampling. The Biometrical Journal. 36(6): 753-764.
[7] Singh, H. P. and Tailor, R. (2003). Use of known correlation coefficient
in estimating the finite population mean. Statistics in Transition. 6 (4):
555-560.
[8] Takahasi K. and Wakimoto, K. (1968). On unbiased estimates of the
population mean based on the sample stratified by means of ordering.
Annals of the Institute of Statistical Mathematics 20: 1-31.
[9] Upadhyaya, L.N. and Singh, H.P. (1999). Use of transformed auxiliary
variable in estimating the finite population mean. Biometrical Journal,
41(5): 627-636.