Modified median quartile double ranked set sampling for estimation of population mean
Muhammad Ahmed Shehzad,
Anam Nisar,
Aamna Khan,
Walid Emam,
Yusra Tashkandy,
Haris Khurram,
Isra Al-Shbeil
Affiliations
Muhammad Ahmed Shehzad
Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan; Corresponding author.
Anam Nisar
Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan
Aamna Khan
Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan
Walid Emam
Department of Statistics and Operations Research, Faculty of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia
Yusra Tashkandy
Department of Statistics and Operations Research, Faculty of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia
Haris Khurram
Department of Sciences & Humanities, National University of Computer and Emerging Sciences, Chiniot-Faisalabad Campus, Pakistan
Isra Al-Shbeil
Department of Mathematics, Faculty of Science, The University of Jordan, Amman, 11942, Jordan; Department of Mathematics and Statistics, University of Ottawa, Ottawa, ON, K1N 6N5, Canada
Environmental monitoring and assessment aim to gather data economically, without bias, using efficient and cost-effective sampling methods. One such traditional method is Ranked Set Sampling (RSS), often employed to achieve observational economy. This article introduces an innovative two-stage sampling approach for ranked set sampling (RSS) to get a more precise estimate of the population mean. Modified Median Quartile Double Ranked Set Sampling (MMQDRSS) highlights the ranked base technique's potential as a cost-effective sampling method. To evaluate the performance of the proposed estimator by using real-life data and conducting a simulation study to compare the relative efficiency of the proposed estimator with some existing methods.
