A New Exponential Ratio-Type Estimator for Population Mean Using Two Auxiliary Variables in Double Sampling
Abstract
In this study, a new exponential ratio-type estimator for estimating the population mean using two auxiliary variables in double sampling is proposed. The bias and mean squared error (MSE) of the proposed estimator are derived. The efficiency of the proposed estimator is compared theoretically with some existing estimators such as the usual sample mean estimator, the classical ratio estimator, and other exponential estimators. An empirical study using real-life data is conducted to examine the performance of the estimator. The results indicate that the proposed estimator has the smallest mean square error and the highest relative efficiency among the estimators considered. Hence, the estimator is recommended for practical applications in survey sampling where auxiliary information is available.
Keywords
Double Sampling, Auxiliary Variable, Exponential Estimator, Ratio Estimator, Mean Square Error.
Citations
IRE Journals:
Faweya, Olanrewaju, Abifade, Victor Oluwatobi, Akinyemi, Oluwadare, Ayodele, Oluwasola Joshua, Oyinloye, Adedeji Adigun "A New Exponential Ratio-Type Estimator for Population Mean Using Two Auxiliary Variables in Double Sampling" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 1795-1799 https://doi.org/10.64388/IREV9I9-1715360
IEEE:
Faweya, Olanrewaju, Abifade, Victor Oluwatobi, Akinyemi, Oluwadare, Ayodele, Oluwasola Joshua, Oyinloye, Adedeji Adigun
"A New Exponential Ratio-Type Estimator for Population Mean Using Two Auxiliary Variables in Double Sampling" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1715360
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
Important Links
For Authors
Volume 8:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 7:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 6:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 5:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 4:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12Volume 3:
Issue 1, Issue 2, Issue 3, Issue 4, Issue 5, Issue 6, Issue 7, Issue 8, Issue 9, Issue 10, Issue 11, Issue 12