Ratio Estimators Using Coefficient of Variation and Coefficient of Correlation
- Prayad Sangngam
Abstract
This paper introduces ratio estimators of the population mean using the coefficient of variation of study variable and auxiliary variables together with the coefficient of correlation between the study and auxiliary variables under simple random sampling and stratified random sampling. These ratio estimators are almost unbiased. The mean square errors of the estimators and their estimators are given. Sample size estimation in both sampling designs are presented. An optimal sample size allocation in stratified random sampling is also suggested. Based on theoretical study, it can be shown that these ratio estimators have smaller MSE than the unbiased estimators. Moreover, the empirical study indicates that these ratio estimators have smallest MSE compared to the existing ones.
- Full Text: PDF
- DOI:10.5539/mas.v8n5p70
Journal Metrics
(The data was calculated based on Google Scholar Citations)
h5-index (July 2022): N/A
h5-median(July 2022): N/A
Index
- Aerospace Database
- American International Standards Institute (AISI)
- BASE (Bielefeld Academic Search Engine)
- CAB Abstracts
- CiteFactor
- CNKI Scholar
- Elektronische Zeitschriftenbibliothek (EZB)
- Excellence in Research for Australia (ERA)
- JournalGuide
- JournalSeek
- LOCKSS
- MIAR
- NewJour
- Norwegian Centre for Research Data (NSD)
- Open J-Gate
- Polska Bibliografia Naukowa
- ResearchGate
- SHERPA/RoMEO
- Standard Periodical Directory
- Ulrich's
- Universe Digital Library
- WorldCat
- ZbMATH
Contact
- Sunny LeeEditorial Assistant
- mas@ccsenet.org