Open Access Open Access  Restricted Access Subscription Access

A Class of Dual to Ratio-cum-Product Estimators of Population Mean Using Known Correlation Coefficient Between Auxiliary Variates

Gajendra K. Vishwakarma, Manish Kumar, Ravendra Singh


This paper presents a class of dual to ratio-cum-product estimators of a finite population mean in simple random sampling using information on the known correlation coefficient between two auxiliary variates. The expressions for the Bias and Mean Square Error (MSE) of the proposed class are obtained up to the first degree of approximation. It has been shown that the proposed class is more efficient than the existing estimators under certain given conditions. An empirical study is also carried out to illustrate the performance of the proposed class of estimators over others.


Study variate, Auxiliary variates, Dual, Bias, Mean Square Error.

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.