@article{article_364476, title={New Ratio Estimators for Estimating Population Mean in Simple Random Sampling using a Coefficient of Variation, Correlation Coefficient and a Regression Coefficient}, journal={Gazi University Journal of Science}, volume={30}, pages={610–621}, year={2017}, author={Lawson, Nuanpan}, keywords={Ratio estimators,Coefficient of variation,Correlation coefficient,Regression coefficient}, abstract={<p>We propose new ratio estimators for estimating population mean using known auxiliary  <span style="font-size: 0.9em;">variables in this paper. To estimate the population mean of the study variable we use a known  </span> <span style="font-size: 0.9em;">population coefficient of variation of the auxiliary variable, correlation coefficient between an  </span> <span style="font-size: 0.9em;">interest variable and an auxiliary variable and also the sample regression coefficient of interest  </span> <span style="font-size: 0.9em;">variable of an auxiliary variable. The expressions for the bias and mean square error (MSE) of  </span> <span style="font-size: 0.9em;">the proposed estimators up to the first order of approximation have been obtained. The  </span> <span style="font-size: 0.9em;">performance of proposed estimators are compared with existing estimators using both  </span> <span style="font-size: 0.9em;">theoretical and empirical data. </span> </p>}, number={4}, publisher={Gazi University}