A new statistical outlet with theoretical and practical insight: Its consideration in civic education and radiation

In this article, the principal importance of population proportion estimation accuracy in survey sampling is taken, particularly in the spheres of science in which the science of the radiation data is required to establish the policy, the testing of safety, and the predictability of the findings in relation to the policy decisions, the safety testing, and predictive modeling. Our primary goal is to develop a new estimator, which will take into consideration the study and auxiliary attributes to increase effectiveness in the estimation process and minimize the impact of non-similarity of observations and distributional discontinuities. Theoretical properties of the estimator such as bias and mean square error (MSE) are derived up to first order approximation. To assess efficiency of estimators, we used some real data sets taken from radiation science and civic education. From the numerical results it has been shown that the suggested estimator provides minimum MSE and higher percentage relative efficiency. This article provides favorable proportion estimator and hence quite appropriate in the uses of radiation science and civic education. Overall, the study is a valid, and functional approximation model that can effectively be applied in the broader scope of the sciences in the support of information on auxiliary bases, and with data quality problems still extant.