Browsing by Author "Audu, A."
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Item ALTERNATIVE TO FACTOR-TYPE ESTIMATOR UNDER SINGLE-PHASE SAMPLING(Katsina Journal of Natural and Applied Sciences, 2016) Audu, A.; Adewara, A. A.In this paper alternative estimator to factor-type estimator for estimating population mean has been proposed using information on population units yet to be drawn from both study and auxiliary variables. The expressions for bias and MSE for the proposed estimator in the form of population parameters using the concept of large sample approximation have been derived and the conditions for its efficiency over the conventional estimators have been established. Also empirical study to demonstrate the efficiencies of the proposed estimator over traditional estimators have been performed and the results show that the proposed estimator is less biased and performed better.Item CLASS OF RATIO ESTIMATORS WITH KNOWN FUNCTIONS OF AUXILIARY VARIABLE FOR ESTIMATING FINITE POPULATION VARIANCE(Asian Journal of Mathematics and Computer Research, 2016) Audu, A.; Adewara, A. A.; Singh, R. V. K.In this paper, we have suggested a class of improved ratio estimators for finite population variance. The proposed class of estimators is obtained by using unknown weight on some existing estimators. The MSE of the proposed estimators have been obtained and the conditions for their efficiency over some existing variance estimators have been established. The present proposed family of finite variance estimators, having obtaining the optimal values of the constants, exhibit significant improvement over the existing estimators. The empirical study is also conducted to corroborate the theoretical results and the results show that the proposed class of estimators is more efficient.Item MODIFICATION OF RATIO ESTIMATOR UNDER TWO PHASE SAMPLING(FUW Trends in Science & Technology Journa, 2018) Kamba, A. I.; Adewara, A. A.; Audu, A.In this paper, modification of Adebola and Adegoke’s report on ratio estimator was suggested. The modified estimator was obtained through transformation in two cases using sample mean of auxiliary variables. Case one was when the second sample was drawn from the first sample why case two was when the second sample was drawn from the population. The bias and mean square error (MSE) of the modified ratio estimator in the two cases were obtained. The theoretical and numerical validity of the modified ratio estimator under the two cases were determined to show its superiority over some considered existing related ratio estimators. Numerical results shows that the modified ratio estimator under the two cases were more efficient than the considered existing related estimatorsItem MODIFIED PRODUCT ESTIMATOR UNDER TWO–PHASE SAMPLING(GLOBAL JOURNAL OF PURE AND APPLIED SCIENCES, 2019) Kamba, A. I.; Adewara, A. A.; Audu, A.In this paper, modification of product estimator under two-phase sampling was suggested. The modified product estimator was obtained through transformation in two cases using sample mean of auxiliary variables. Case one was when the second sample was drawn from the first sample while case two was when the second sample was drawn from the population. The bias and mean square error (MSE) of the modified product estimator was obtained. The theoretical and numerical validity of the modified product estimator under the two cases were determined to show it superiority to some considered existing product estimators. Numerical results shows that the modified product estimator under the two cases were more efficient than the considered existing estimators.Item MODIFIED RATIO-CUM-PRODUCT ESTIMATORS OF POPULATION MEAN IN LINEAR SYTEMATIC SAMPLING UNDER TWO-PHASE SAMPLING SCHEME(FUW Trends in Science & Technology Journal, 2019) Abioye, J. O.; Adewara, A. A.; Audu, A.; Amoyedo, F. E.This paper is basically aimed at suggesting two modified ratio-cum-product estimators having two auxiliary variables, under the linear systematic sampling. These suggested ratio-cum-product modified estimators under the two-phase sampling scheme were suggested using linear transformation technique, the biases and mean squared errors (MSEs) of the corresponding modified estimators under cases I and II were derived and established (where Case I refers to the case whereby the second sample is drawn from the first sample and Case II refers to the case whereby the second sample is drawn from the main population under study), the efficiency conditions under which the two modified estimators would be more efficient than relative existing ones were derived and established and the relative efficiency of these modified estimators were empirically determined and established using five real life data sets which were obtained from various sources. From the results of the empirical study using real life data sets, it was concluded that the suggested modified estimators in this study demonstrated high relative efficiency over existing related estimators