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Cody, R. D. – Journal of Geological Education, 1972
Presents the derivation of rotation and reflection matrix representation of symmetry operators as used in the initial discussion of crystal symmetry in elementary mineralogy at Iowa State University. Includes references and an appended list of matrix representations of the important crystallographic symmetry operators, excluding the trigonal and…
Descriptors: College Science, Earth Science, Geology, Mathematical Models
Johnson, Raymond L.; Wall, Donald D. – Educ Psychol Meas, 1969
Descriptors: Geometric Concepts, Mathematical Models, Measurement Techniques, Psycholinguistics
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Hendry, I. C. – Long Range Planning, 1972
A forecasting method using an estimate of ultimate level of adoption and expected time scale. (RA)
Descriptors: Adoption (Ideas), Mathematical Models, Planning, Prediction
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Krauze, Tadeusz K.; Hillinger, Claude – Journal of the American Society for Information Science, 1971
A mathematical model is presented which explains the observed exponential growth rates of citations and references in a scientific discipline. The independent variables are the growth rate of the number of articles published and the decay rate of citation of old literature. (13 references) (Author)
Descriptors: Citations (References), Growth Patterns, Mathematical Models, Scholarly Journals
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Samuelson, Paul A. – Science, 1971
This Nobel lecture describes the development and role of maximum principles in economic research as practiced by the author. (AL)
Descriptors: Economic Research, Economics, Mathematical Models, Research Reviews (Publications)
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Davies, D. R. – Mathematical Spectrum, 1971
Descriptors: Climate, Computers, Mathematical Applications, Mathematical Models
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Levin, Martin L. – Simulation and Games, 1970
Descriptors: Adolescents, Mathematical Models, Political Socialization, Simulation
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Dickson, E. M. – Bioscience, 1970
Descriptors: Contraception, Demography, Family Planning, Mathematical Models
Schutz, Robert W. – Research Quarterly of the AAHPER, 1970
Descriptors: Athletics, Evaluation, Mathematical Models, Performance Factors
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Eastwood, Margaret – Mathematics in School, 1983
Models for developing addition, subtraction, and multiplication with integers are given. (MNS)
Descriptors: Integers, Mathematical Models, Mathematics, Mathematics Instruction
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Dunn, Terrence R.; Harshman, Richard A. – Psychometrika, 1982
The kinds of individual differences in perceptions permitted by the weighted euclidean model for multidimensional scaling are more restrictive than those allowed by models developed by Tucker or Carroll. It is shown how problems which occur when using the more general models can be removed. (Author/JKS)
Descriptors: Data Analysis, Individual Differences, Mathematical Models, Multidimensional Scaling
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Buell, Duncan A. – Information Processing and Management, 1981
Discusses several query-processing methods designed to allow the use of relevance weights or thresholds attached to terms and compares them with normal Boolean rules and fuzzy subset theory. Forty-five references are listed. (FM)
Descriptors: Information Retrieval, Mathematical Models, Online Systems, Search Strategies
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Friedman, Sally; Weisberg, Herbert F. – Educational and Psychological Measurement, 1981
The first eigenvalue of a correlation matrix indicates the maximum amount of the variance of the variables which can be accounted for with a linear model by a single underlying factor. The first eigenvalue measures the primary cluster in the matrix, its number of variables and average correlation. (Author/RL)
Descriptors: Correlation, Mathematical Models, Matrices, Predictor Variables
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Shapiro, Alexander – Psychometrika, 1982
The extent to which one can reduce the rank of a symmetric matrix by only changing its diagonal entries is discussed. Extension of this work to minimum trace factor analysis is presented. (Author/JKS)
Descriptors: Data Analysis, Factor Analysis, Mathematical Models, Matrices
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Wilcox, Rand R. – Educational and Psychological Measurement, 1981
A formal framework is presented for determining which of the distractors of multiple-choice test items has a small probability of being chosen by a typical examinee. The framework is based on a procedure similar to an indifference zone formulation of a ranking and election problem. (Author/BW)
Descriptors: Mathematical Models, Multiple Choice Tests, Probability, Test Items
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