http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/70 Statistics 2026-06-11T11:46:20Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31274 Title: Calibration Approach to Developed Triple Means Estimators Authors: Usman, A; Haruna, S; Yakubu, YU. Y; Baba Abstract: Calibration estimation has become a ubiquitous methodology across diverse fields, providing a foundational framework for tackling complex statistical problems. Its significance In recent years, has emerged as a pivotal topic in research on estimation in survey sampling where it has emerged as a crucial area of study. By providing a systematic approach to integrating auxiliary information, calibration enhances the estimation procedure, rendering it a valuable tool in statistical analysis. The article propounds an calibration approaches of triple mean under simple random sampling of variance estimators, the proposed calibration have been Corresponding author: E-mail: sharunakutigi@gmail.com; Cite as: Suleiman Haruna, Yisa Yakubu, Usman Abubakar, and Usman Yahaya Baba. 2025. “Calibration Approach to Developed Triple Means Estimators”. Asian Research Journal of Mathematics 21 (11):76–91. https://doi.org/10.9734/arjom/2025/v21i111013. Haruna et al.; Asian Res. J. Math., vol. 21, no. 11, pp. 76-91, 2025; Article no.ARJOM.146587 develop utilizing sample variance incorporation with existing estimators of AM, GM, HM, in the problem constraints of the optimization in other to contribute effectively to new design calibrated weight. However, the proposed new weight is obtained using most common approach Lagrange function with two multipliers. The motivation for using calibration scheme is due to their ability in reduce bias and means square error, enhance precision, base on how auxiliary variable are been utilized, provide flexibility, comply with standard and improve decision making. Focusing on simulated data approached using exponential and beta the result indicate superiority of classes calibrated estimators of studied via R packages. 2025-01-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31269 Title: Investigation of Some Features Inherent in Analysis of Variance and one of its Variants in the Multivariate Setting Authors: Usman, A; Adeleke, B. L; Adeleke, M. O Abstract: It is common to have experiments conducted with the quest to seek an option in the use of analysis of variance (ANOVA) as incontrovertible choice among experimenters. The validity of this quest has been responsible for the considerable attention that has been given to the use of ANOVA. Different Types of experiments may throw up one or more response variable. With one response variable, the ANOVA option is indeed appropriate. However, for the simplicity of ANOVA the experimenter may have to contend with the somewhat a variant of it, even when the use of more than one response variable becomes expedient. The foregoing situation will be in violation of some well establishment ground norm of the need to overcome burdensome computations. This paper therefore presents a number of situations for the purpose of unveiling the inherent forms of statistics that are required to be computed. Although these statistics may appear to be burdensome or complicated in forms as they may present themselves in the setting of Multivariate ANOVA (MANOVA), which in reality has the other side of considerable reduction in the number of various statistics that are required to be computed. Such statistics are the sums of squares and sum of products for the two distinct independent components, in both the treatment and error, that the total sums of squares and products (SSPM) in the MANOVA has to be split into. Ditto, for the ANOVA that has its total sums of squares (SS), to be split into two orthogonal parts of treatment and error respectively. Furthermore, the appropriate number of independent components in which the treatment component will be partitioned is indeed determined by the number of factors say k, with the corresponding labels A1, A2, … , Ak, that the experimenter may have to adopt. A number of examples were presented for the illustration of distinct features inherent in both the ANOVA and MANOVA. 2022-01-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31267 Title: Response Surface Methodology and Its Application in Evaluating Scientific Activities in a Federal University of Technology Authors: Usman, A; Abdullahi, U; Bello, A. O; Akanji, O .D; Adetutu, O. M Abstract: This paper used a second-order response surface methodology (RSM) to modeled the relationship between some selected university ranking indicators and citation variables. The objectives were to investigate which of the selected indicator(s) are relevant to the number of citations received on publication and obtain the best link function that relate the factors variables to response variable, also check if there exist an interaction effect between the selected ranking indicators. The University ranking indicators used in this paper were sourced from google scholar, research gate, the University repository and through questionnaire. The observations were treated as quasi experimental designs. The causal effect of Publication was funding, collaboration, human resources, department facility, which were highly significant. Also, the causal effect for Citation were numbers of articles, collaboration, undergraduate and postgraduate project were highly significant and follow second order model with interaction. The obtained model was used to fit possible _____________________________________________________________________________________________________ *Corresponding author: E-mail: u.abdullahi@futminna.edu.ng; Curr. J. Appl. Sci. Technol., vol. 41, no. 48, pp. 23-34, 2022 Abullahi et al.; Curr. J. Appl. Sci. Technol., vol. 41, no. 48, pp. 23-34, 2022; Article no.CJAST.86581 number of publication and citation ( ) for differently assumed factors and graphical method was used to compare each paired factors to the number of citations on 3D plots. Using contours plot and surface plot highest citation is reached only in department with high production, human resources, funds, facilities and more collaboration. Based on these results, it is recommended that, research collaboration among the university researchers should be highly encourage, and there should be a provision for more facility in the department in other to maximize research output of the departments. Keywords: R 2022-01-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31265 Title: Mixed-optimum Estimators for Estimating Finite Population Mean in the Presence of Outliers Using Auxiliary Variable under Simple Random Sampling Authors: Usman, A; Kawai, H. E; Yakubu, Y; Isah, A Abstract: In sample survey the nature of correlation between the study and auxiliary variables plays a crucial role in improving the accuracy of the estimates. In this study a generalized mixed-optimum estimators that handle the three nature of correlation for different values (-1,0,1) of the scalar was proposed for estimating the finite population mean when there is information on the minimum and maximum values of the auxiliary variable and when both the auxiliary and study variables exhibit extreme values. The expression for the mean squared errors and biases were derived to the first order of approximation. The performance of the proposed estimators, relative to conventional methods, has been rigorously analyzed, revealing notable improvements. ________________________________________ *Corresponding author: Email: mekanwai3@gmail.com; Cite as: Kanwai, M.E, Y. Yakubu, A. Isah, and A. Usman. 2024. “Mixed-Optimum Estimators for Estimating Finite Population Mean in the Presence of Outliers Using Auxiliary Variable under Simple Random Sampling”. Asian Journal of Probability and Statistics 26 (12):1-14. https://doi.org/10.9734/ajpas/2024/v26i12679. Kanwai et al.; Asian J. Prob. Stat., vol. 26, no. 12, pp. 1-14, 2024; Article no.AJPAS.126778 Theoretical analysis confirmed that correcting the estimators for mitigating maximum and minimum values enhanced its efficiency, and these findings have been empirically validated through comprehensive numerical analysis. 2024-01-01T00:00:00Z