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Dixon, David A.; Shafer, Richard H. – Journal of Chemical Education, 1973
Descriptors: Chemistry, College Science, Computer Assisted Instruction, Instruction
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Landau, D. P.; Alben, R. – American Journal of Physics, 1973
A description is given in which a computer program can be used to illustrate principles of statistical mechanics. The concepts of ensembles, statistical averages, and responses are classified particularly with respect to the role of statistical fluctuations. (DF)
Descriptors: College Science, Computer Assisted Instruction, Computer Programs, Instruction
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Hinders, Duane C. – Mathematics Teacher, 1981
The uses of random number generators are illustrated in three ways: (1) the solution of a probability problem using a coin; (2) the solution of a system of simultaneous linear equations using a die; and (3) the approximation of pi using darts. (MP)
Descriptors: Algebra, Educational Games, Learning Activities, Monte Carlo Methods
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You, Soon-Hyung; Stone-Romero, Eugene F. – Educational and Psychological Measurement, 1996
To clarify the findings of R. Gillett (1991) about the inequality of the means of test scores of minority and majority examinees, the standard errors of the quota-selected sample means and the sampling distribution of these means were studied through Monte Carlo simulation. Results explain that the quota selection inequality results from…
Descriptors: Error of Measurement, Minority Groups, Monte Carlo Methods, Sampling
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Bandalos, Deborah L. – Structural Equation Modeling, 1997
Monte Carlo methods were used to study the accuracy and utility of estimators of overall error and error due to approximation in structural equation modeling. Effects of sample size, indicator reliabilities, and degree of misspecification were examined. The rescaled noncentrality parameter also was examined. Choosing among competing models is…
Descriptors: Comparative Analysis, Error of Measurement, Estimation (Mathematics), Monte Carlo Methods
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Harwell, Michael R. – Educational and Psychological Measurement, 1997
Results from two Monte Carlo studies in item response theory (comparisons of computer item analysis programs and Bayes estimation procedures) are analyzed with inferential methods to illustrate the procedures' strengths. It is recommended that researchers in item response theory use both descriptive and inferential methods to analyze Monte Carlo…
Descriptors: Bayesian Statistics, Comparative Analysis, Computer Software, Estimation (Mathematics)
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Cohen, Jon; Snow, Stephanie – Journal of Educational Measurement, 2002
Studied the impact of changes in item difficulty on National Assessment of Educational Progress (NAEP) estimates over time through a Monte Carlo study that simulated the responses of 1990 NAEP mathematics respondents to 1990 and 1996 NAEP mathematics items. Results support the idea that these changes have not affected the NAEP trend line.…
Descriptors: Change, Difficulty Level, Estimation (Mathematics), Mathematics Tests
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Smith, Rachel A.; Levine, Timothy R.; Lachlan, Kenneth A.; Fediuk, Thomas A. – Human Communication Research, 2002
Notes that the availability of statistical software packages has led to a sharp increase in use of complex research designs and complex statistical analyses in communication research. Reports a series of Monte Carlo simulations which demonstrate that this complexity may come at a heavier cost than many communication researchers realize. Warns…
Descriptors: Analysis of Variance, Communication Research, Computer Software, Higher Education
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Bell, D. A.; And Others – Journal of the American Society for Information Science, 1990
Investigates the value of applying principles derived from simulated annealing to clustering tuples in database design, and compares this technique with a graph-collapsing clustering method. It is concluded that, while the new method does give superior results, the expense involved in algorithm run time is prohibitive. (24 references) (CLB)
Descriptors: Algorithms, Comparative Analysis, Computer Simulation, Cost Effectiveness
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Guell, Oscar A.; Holcombe, James A. – Analytical Chemistry, 1990
Described are analytical applications of the theory of random processes, in particular solutions obtained by using statistical procedures known as Monte Carlo techniques. Supercomputer simulations, sampling, integration, ensemble, annealing, and explicit simulation are discussed. (CW)
Descriptors: Chemical Analysis, Chemistry, College Science, Computer Simulation
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Chou, Chih-Ping; Bentler, P. M. – Multivariate Behavioral Research, 1990
The empirical performance under null/alternative hypotheses of the likelihood ratio difference test (LRDT); Lagrange Multiplier test (evaluating the impact of model modification with a specific model); and Wald test (using a general model) were compared. The new tests for covariance structure analysis performed as well as did the LRDT. (RLC)
Descriptors: Analysis of Covariance, Comparative Analysis, Hypothesis Testing, Mathematical Models
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Storms, Gert – Psychometrika, 1995
A Monte Carlo study was conducted to investigate the robustness of the assumed error distribution in maximum likelihood estimation models for multidimensional scaling. Results show that violations of the assumed error distribution have virtually no effect on the estimated distance parameters. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Maximum Likelihood Statistics, Monte Carlo Methods
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Bacon, Donald R. – Multivariate Behavioral Research, 1995
A maximum likelihood approach to correlational outlier identification is introduced and compared to the Mahalanobis D squared and Comrey D statistics through Monte Carlo simulation. Identification performance depends on the nature of correlational outliers and the measure used, but the maximum likelihood approach is the most robust performance…
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Estimation (Mathematics)
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Ichikawa, Masanori – Psychometrika, 1992
Asymptotic distributions of the estimators of communalities are derived for the maximum likelihood method in factor analysis. It is shown that equating the asymptotic standard error of the communality estimate to the unique variance estimate is not correct for the unstandardized case. Monte Carlo simulations illustrate the study. (SLD)
Descriptors: Computer Simulation, Equations (Mathematics), Estimation (Mathematics), Factor Analysis
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Tracz, Susan M.; And Others – Educational and Psychological Measurement, 1992
Effects of violating the independence assumption when combining correlation coefficients in a meta-analysis were studied. This Monte-Carlo simulation varied sample size, predictor number, population intercorrelation among predictors, and population correlation between predictors and criterion. Combining statistics from nonindependent data in a…
Descriptors: Computer Simulation, Correlation, Equations (Mathematics), Mathematical Models
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