This research article develops the exponential type estimators for estimating the population mean using conventional and non-conventional auxiliary parameters under ranked set sampling \(\left( {RSS} \right)\) technique. The bias and mean square error of the developed estimators have been calculated up to the linear approximation. The conditions have been derived for optimizing the value of mean square error and then the minimum value of mean square has been obtained. Theoretical comparisons have been made with the relevant literary estimators in terms of efficiency and conditions have been derived under which the developed estimators perform more efficiently. Empirically by using real data sets, the effectiveness of the developed estimator over the literary estimators has been justified. Also, the preference of ranked set sampling over simple random sampling without replacement (SRSwor) is recommended on the basis of empirical results.
