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On improvement in estimating the population mean in simple random sampling

Author

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  • Sat Gupta
  • Javid Shabbir

Abstract

Kadilar and Cingi [Ratio estimators in simple random sampling, Appl. Math. Comput. 151 (3) (2004), pp. 893-902] introduced some ratio-type estimators of finite population mean under simple random sampling. Recently, Kadilar and Cingi [New ratio estimators using correlation coefficient, Interstat 4 (2006), pp. 1-11] have suggested another form of ratio-type estimators by modifying the estimator developed by Singh and Tailor [Use of known correlation coefficient in estimating the finite population mean, Stat. Transit. 6 (2003), pp. 655-560]. Kadilar and Cingi [Improvement in estimating the population mean in simple random sampling, Appl. Math. Lett. 19 (1) (2006), pp. 75-79] have suggested yet another class of ratio-type estimators by taking a weighted average of the two known classes of estimators referenced above. In this article, we propose an alternative form of ratio-type estimators which are better than the competing ratio, regression, and other ratio-type estimators considered here. The results are also supported by the analysis of three real data sets that were considered by Kadilar and Cingi.

Suggested Citation

  • Sat Gupta & Javid Shabbir, 2008. "On improvement in estimating the population mean in simple random sampling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(5), pages 559-566.
    • Handle: RePEc:taf:japsta:v:35:y:2008:i:5:p:559-566
    DOI: 10.1080/02664760701835839
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    Citations

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    Cited by:

    1. Giancarlo Diana & Marco Giordan & Pier Perri, 2011. "An improved class of estimators for the population mean," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(2), pages 123-140, June.
    2. Ndlovu N & Mafumbate J & Mafuka A & Brena M, 2017. "The Impact of the Buy Zimbabwe Campaign on Performance of Zimbabwean Companies in the Retail Sector," Journal of Economics and Behavioral Studies, AMH International, vol. 8(6), pages 227-236.
    3. Sardar Hussain & Sohaib Ahmad & Mariyam Saleem & Sohail Akhtar, 2020. "Finite population distribution function estimation with dual use of auxiliary information under simple and stratified random sampling," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-30, September.
    4. G. N. Singh & D. Majhi, 2014. "Some Chain-type Exponential Estimators of Population Mean in Two-Phase Sampling," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(2), pages 221-230, March.
    5. Evangelia Karasmanaki & Spyros Galatsidas & Georgios Tsantopoulos, 2024. "Socioeconomic Factors Driving the Transition to a Low-Carbon Energy System," Energies, MDPI, vol. 17(14), pages 1-15, July.
    6. Kumari Priyanka & Pidugu Trisandhya & Richa Mittal, 2018. "Dealing sensitive characters on successive occasions through a general class of estimators using scrambled response techniques," METRON, Springer;Sapienza Università di Roma, vol. 76(2), pages 203-230, August.
    7. Ramkrishna Solanki & Housila Singh, 2015. "Efficient classes of estimators in stratified random sampling," Statistical Papers, Springer, vol. 56(1), pages 83-103, February.
    8. Surya K. Pal & Housila P. Singh, 2017. "Estimation of finite population mean using auxiliary information in systematic sampling," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1392-1398, November.

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