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Makar, Katie; Allmond, Sue – ZDM: The International Journal on Mathematics Education, 2018
Children have limited exposure to statistical concepts and processes, yet researchers have highlighted multiple benefits of experiences in which they design and/or engage informally with statistical modelling. A study was conducted with a classroom in which students developed and utilised data-based models to respond to the inquiry question,…
Descriptors: Statistics, Mathematical Models, Prediction, Statistical Distributions
Vogt, Paul – Cognitive Science, 2012
Cross-situational learning has recently gained attention as a plausible candidate for the mechanism that underlies the learning of word-meaning mappings. In a recent study, Blythe and colleagues have studied how many trials are theoretically required to learn a human-sized lexicon using cross-situational learning. They show that the level of…
Descriptors: Vocabulary Development, Learning, Mathematical Models, Robustness (Statistics)
Si, Yajuan; Reiter, Jerome P. – Journal of Educational and Behavioral Statistics, 2013
In many surveys, the data comprise a large number of categorical variables that suffer from item nonresponse. Standard methods for multiple imputation, like log-linear models or sequential regression imputation, can fail to capture complex dependencies and can be difficult to implement effectively in high dimensions. We present a fully Bayesian,…
Descriptors: Nonparametric Statistics, Bayesian Statistics, Measurement, Evaluation Methods
Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
Phelps, James L. – Educational Considerations, 2012
In most school achievement research, the relationships between achievement and explanatory variables follow the Newton and Einstein concept/principle and the viewpoint of the macro-observer: Deterministic measures based on the mean value of a sufficiently large number of schools. What if the relationships between achievement and explanatory…
Descriptors: Academic Achievement, Computation, Probability, Statistics
Bruno, A.; Espinel, M. C. – International Journal of Mathematical Education in Science and Technology, 2009
This article details the results of a written test designed to reveal how education majors construct and evaluate histograms and frequency polygons. Included is a description of the mistakes made by the students which shows how they tend to confuse histograms with bar diagrams, incorrectly assign data along the Cartesian axes and experience…
Descriptors: Education Majors, Mathematical Models, Statistical Distributions, Geometric Concepts

Chen, Ye-Sho; Leimkuhler, Ferdinand F. – Information Processing and Management, 1987
This analysis of Zipf's law uses an index for the sequence of observed values of the variables in a Zipf-type relationship. Three important properties relating rank, count, and frequency are identified, shapes of Zipf-type curves are described, and parameters of the Mandelbrot-Zipf law are discussed. (Author/LRW)
Descriptors: Indexing, Mathematical Models, Predictor Variables, Statistical Distributions

Hofacker, Charles F. – Multivariate Behavioral Research, 1984
An alternative for analyzing responses to Likert Scales is proposed, using additive conjoint measurement. It assumes that subjects can report their attitudes toward stimuli in rank order. Neither within-subject nor between-subject distributional assumptions are made. Nevertheless, interval level stimulus values and response category boundaries are…
Descriptors: Attitude Measures, Mathematical Models, Responses, Statistical Analysis

Rousseau, Ronald – Journal of the American Society for Information Science, 1992
Proposes a mathematical model to explain the observed concentration or diversity of nominal classes in information retrieval systems. The Lorenz Curve is discussed, Information Production Process (IPP) is explained, and a heuristic explanation of circumstances in which the model might be used is offered. (30 references) (LRW)
Descriptors: Heuristics, Information Retrieval, Mathematical Models, Research Needs

Rousseau, Ronald – Information Processing and Management, 1992
This article offers comments and clarifications of Egghe's paper, which dealt with information production processes (IPP) and the Gini index. Topics addressed include the length of the Lorenz curve as a concentration measure, the discrete duality operator, and a Bradford-Leimkuhler distribution. (10 references) (LRW)
Descriptors: Information Science, Mathematical Formulas, Mathematical Models, Measurement Techniques
Luh, Wei-Ming; Olejnik, Stephen – 1990
Two-stage sampling procedures for comparing two population means when variances are heterogeneous have been developed by D. G. Chapman (1950) and B. K. Ghosh (1975). Both procedures assume sampling from populations that are normally distributed. The present study reports on the effect that sampling from non-normal distributions has on Type I error…
Descriptors: Comparative Analysis, Mathematical Models, Power (Statistics), Sample Size
Schmalz, Steve W.; Cartledge, Carolyn M. – 1982
During the last decade the use of Bayesian statistical method has become quite prevalent in the educational community. Yet, like most statistical techniques, little has been written concerning the application of these methods to the classroom setting. The purpose of this paper is to help correct such a deficiency in the literature by developing a…
Descriptors: Bayesian Statistics, Classroom Techniques, Mastery Tests, Mathematical Models

Nicholls, Paul Travis – Information Processing and Management, 1988
Presents Price's law, which states that half of the literature on a subject will be contributed by the square root of total number of authors publishing in that area, and assesses it against empirical evidence and simulated productivity distributions. The discussion covers this law's relation to Lotka's law and its empirical validity. (Author/CLB)
Descriptors: Bibliometrics, Hypothesis Testing, Mathematical Models, Proof (Mathematics)

Bloxom, Bruce – Psychometrika, 1985
The use of semiparametric models may require incorporating additional functions which do not vary across distributions and may require expressing the models in terms of the joint distribution of response class and response time. (Author/LMO)
Descriptors: Mathematical Models, Psychometrics, Reaction Time, Regression (Statistics)

Grass, Alan L.; Perry, Philippa – Psychometrika, 1983
A procedure for inferring the validity of a selection test as a predictor of some criterion when the available data are limited due to prior selection is described. (Author/JKS)
Descriptors: Mathematical Models, Predictive Measurement, Predictive Validity, Selection