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Vinay Kumar Yadav; Shakti Prasad – Measurement: Interdisciplinary Research and Perspectives, 2024
In sample survey analysis, accurate population mean estimation is an important task, but traditional approaches frequently ignore the intricacies of real-world data, leading to biassed results. In order to handle uncertainties, indeterminacies, and ambiguity, this work presents an innovative approach based on neutrosophic statistics. We proposed…
Descriptors: Sampling, Statistical Bias, Predictor Variables, Predictive Measurement
Foy, Pierre, Ed.; Arora, Alka, Ed.; Stanco, Gabrielle M., Ed. – International Association for the Evaluation of Educational Achievement, 2013
This supplement contains documentation on the explicit and implicit stratification variables included in the TIMSS 2011 data files. The explicit strata are smaller sampling frames, created from the national sampling frames, from which national samples of schools were drawn. The implicit strata are nested within the explicit strata, and were used…
Descriptors: Predictor Variables, Sampling, Comparative Education, International Education
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Watkins, Ann E.; Bargagliotti, Anna; Franklin, Christine – Journal of Statistics Education, 2014
Although the use of simulation to teach the sampling distribution of the mean is meant to provide students with sound conceptual understanding, it may lead them astray. We discuss a misunderstanding that can be introduced or reinforced when students who intuitively understand that "bigger samples are better" conduct a simulation to…
Descriptors: Simulation, Sampling, Sample Size, Misconceptions
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Bakir, Saad T. – American Journal of Business Education, 2010
We propose a nonparametric (or distribution-free) procedure for testing the equality of several population variances (or scale parameters). The proposed test is a modification of Bakir's (1989, Commun. Statist., Simul-Comp., 18, 757-775) analysis of means by ranks (ANOMR) procedure for testing the equality of several population means. A proof is…
Descriptors: Majors (Students), Grade Point Average, Nonparametric Statistics, Business Administration Education
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Fuhr, Norbert; Huther, Hubert – Information Processing and Management, 1989
Discusses the interdependencies between parameter estimation and properties of probabilistic models, such as dependency assumptions, binary vs. nonbinary features, and estimation sample selection. An optimum estimation for binary features applicable to information retrieval is defined, a method for computing this estimation using empirical data is…
Descriptors: Estimation (Mathematics), Information Retrieval, Mathematical Models, Predictor Variables
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Broodbooks, Wendy J.; Elmore, Patricia B. – Educational and Psychological Measurement, 1987
The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model, and principal axes factor analyses were performed. (Author/LMO)
Descriptors: Factor Analysis, Mathematical Models, Monte Carlo Methods, Predictor Variables