Ratio Estimator of Population Mean using Quartile and Skewness Coefficient

Abstract

Simple random sampling is random sampling, where each element has the same opportunity to be chosen from the population. An estimator is said to be good if it has high accuracy and precision value. The accuracy value is related to the extent to which the average of an estimated value deviates from the measured parameter value and the precision value is related to the extent of the spread of a parameter estimator. The accuracy value of an estimator is said to be good if the expected value of the sample statistics is not biased and the precision value of an estimator is said to be good if it has a small variance value. This study aims to determine the ratio estimator for population averages in simple random sampling using quartile information and the skewness coefficient of additional variables that are assumed to provide information to the character being studied. The two estimator methods are biased estimators and mean square error (MSE). Both estimators are determined through Taylor's approach. From the results of the comparative analysis it was found that for the MSE of each estimator it was found that for the  estimator it was an efficient estimator. This comparison shows that the  estimator using the skewness coefficient is more efficient than the  estimator using the skewness coefficient.