Authors : Oke Samuel A; Adesina Oluwaseun A; Oladimeji Lukman A; Akinade Oludayo O; OguntolaToyin O; Tijani Rokibat A; Adegoke Maryam A
Volume/Issue : Volume 8 - 2023, Issue 7 - July
Google Scholar : https://bit.ly/3TmGbDi
Scribd : https://tinyurl.com/y28dyp88
DOI : https://doi.org/10.5281/zenodo.8224226
This study aims to explore the preference
order regarding the utilization of different estimation
methods in sample surveys. Through empirical analysis,
the research examines both the conventional simple
random sampling without replacement estimator and the
efficiency of double sampling for ratio and regression
estimators. The objective is to identify the methods that
the estimator is the most efficient.
Double sampling procedure was adopted, and
comparing the minimum variances empirically which was
used to obtain the most efficient estimator using the data
collected from the variable of interest (expenditure) and
the auxiliary variable (salary). In the first phase, a sample
size of (150, 120, 80, and 60) was chosen from the
population and in the second phase a subsample of size
(70, 55, 45, and 30) was selected from the first phase, each
at four different levels (1, 2, 3 and 4) without replacement.
Of the three sampling methods, namely double
sampling for ratio estimator, simple random sample
without replacement, and double sampling for regression
estimator, the last one shows the least variability, making
it the most effective estimator in terms of efficiency.
Consequently, when the auxiliary variable is accessible, it
is advisable to utilize the double sampling for regression
method in order to enhance the accuracy of estimating the
population parameter.
Keywords : Double sampling, ratio estimator, regression estimator, simple random sampling without Replacement, minimum variances.