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Kazak, Sibel; Pratt, Dave – Research in Mathematics Education, 2021
We examine the challenges of teaching probability through the use of modelling. We argue how an integrated modelling approach might facilitate a coordinated understanding of distribution by marrying theoretical and data-oriented perspectives and present probability as more connected to the social lives of modern-day students. Research is, however,…
Descriptors: Teaching Methods, Mathematics Instruction, Faculty Development, Probability
Weintrop, David; Beheshti, Elham; Horn, Michael; Orton, Kai; Jona, Kemi; Trouille, Laura; Wilensky, Uri – Journal of Science Education and Technology, 2016
Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include "computational thinking" as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new…
Descriptors: Secondary School Mathematics, Secondary School Science, High School Students, Mathematics Education
English, Lyn D. – Mathematics Education Research Journal, 2010
An educational priority of many nations is to enhance mathematical learning in early childhood. One area in need of special attention is that of statistics. This paper argues for a renewed focus on statistical reasoning in the beginning school years, with opportunities for children to engage in data modelling activities. Such modelling involves…
Descriptors: Young Children, Science Curriculum, Mathematical Models, Mathematics Instruction
Perry, Zvi H.; Todder, Doron – Teaching Mathematics and Its Applications: An International Journal of the IMA, 2009
A PUBMED search for "mathematical models in medicine" shows more than 15,000 articles covering almost every field of medicine. We designed a course with the goal of developing the students' skills in computerized data analysis and mathematical modelling, as well as enhancing their ability to read and interpret mathematical data analysis. The study…
Descriptors: Medical Education, Medical Students, Mathematics Education, Student Attitudes

Yung, Yiu-Fai – Psychometrika, 1997
Various types of finite mixtures of confirmatory factor analysis models are proposed for handling data heterogeneity. Proposed classes of mixture models differ in their unique representations of data heterogeneity, and three sampling schemes for these mixtures are distinguished. Advantages of the Approximate Scoring method are outlined. (SLD)
Descriptors: Data Analysis, Mathematical Models, Sampling, Scoring

Hedges, Larry V.; Olkin, Ingram – Psychometrika, 1981
Commonality components have been defined as a method of partitioning squared multiple correlations. The asymptotic joint distribution of all possible squared multiple correlations is derived. The asymptotic joint distribution of linear combinations of squared multiple correlations is obtained as a corollary. (Author/JKS)
Descriptors: Correlation, Data Analysis, Mathematical Models, Multiple Regression Analysis

DeSarbo, Wayne S. – Psychometrika, 1981
Canonical correlation and redundancy analysis are two approaches to analyzing the interrelationships between two sets of measurements made on the same variables. A component method is presented which uses aspects of both approaches. An empirical example is also presented. (Author/JKS)
Descriptors: Correlation, Data Analysis, Factor Analysis, Mathematical Models

Rindskopf, David – Psychometrika, 1992
A general approach is described for the analysis of categorical data when there are missing values on one or more observed variables. The method is based on generalized linear models with composite links. Situations in which the model can be used are described. (SLD)
Descriptors: Algorithms, Classification, Data Analysis, Estimation (Mathematics)

Muthen, Bengt O. – Psychometrika, 1989
The problems posed for latent variable analysis by populations with different sets of parameter values are discussed. An overview of methodology to address heterogeneity is presented, including a review of structural modeling by the multiple indicator-multiple causes model and the use of the LISCOMP computer program. (SLD)
Descriptors: Data Analysis, Equations (Mathematics), Estimation (Mathematics), Mathematical Models
Yannibelli, Virginia; Godoy, Daniela; Amandi, Analia – Interactive Learning Environments, 2006
Learning styles encapsulate the preferences of the students, regarding how they learn. By including information about the student learning style, computer-based educational systems are able to adapt a course according to the individual characteristics of the students. In accomplishing this goal, educational systems have been mostly based on the…
Descriptors: Student Characteristics, Mathematical Models, Genetics, Educational Technology
Tirri, Henry; And Others – 1997
Methodological issues of using a class of neural networks called Mixture Density Networks (MDN) for discriminant analysis are discussed. MDN models have the advantage of having a rigorous probabilistic interpretation, and they have proven to be a viable alternative as a classification procedure in discrete domains. Both classification and…
Descriptors: Classification, Data Analysis, Discriminant Analysis, Educational Research
Reed, Donald B.; Furman, Gail Chase – 1992
The use of the 2 x 2 matrix in qualitative data analysis and theory generation is discussed, embracing the perspective that the objective of qualitative research in general and the analysis of qualitative data in particular is the development of theory. A 2 x 2 matrix is considered to be a tabular representation of the relationship of two…
Descriptors: Data Analysis, Factor Structure, Mathematical Models, Matrices

Hedges, Larry V. – Journal of Educational Statistics, 1981
Glass's estimator of effect size, the sample mean difference divided by the sample standard deviation, is studied in the context of an explicit statistical model. The exact distribution of Glass's estimator is obtained and the estimator is shown to have a small sample bias. Alternatives are proposed and discussed. (Author/JKS)
Descriptors: Data Analysis, Error of Measurement, Mathematical Models, Research Design

Heth, C. Donald – Psychological Review, 1991
A formal model is presented of the statistical properties of molecular behavioral matching. The model indicates that aggregation effects should be controlled in analysis of matching and that comparison of molecular theories of matching performance affords ideographic analysis of choice behavior. (SLD)
Descriptors: Comparative Analysis, Data Analysis, Decision Making, Equations (Mathematics)

Luftig, Jeffrey T. – Journal of Studies in Technical Careers, 1983
This article reviews some of the less well-known hypothesis tests for variance, how they are employed, and how the results may be interpreted. Tests include testing for a single variance and the T-test for correlated variances. (CT)
Descriptors: Analysis of Variance, Data Analysis, Hypothesis Testing, Mathematical Models