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Showing 1 to 15 of 22 results Save | Export
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Woods, Carol M. – Applied Psychological Measurement, 2008
In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters. In extant Monte Carlo evaluations of RC-IRT, the item response function (IRF) used to fit the data is the same one used to generate the data. The present simulation study examines RC-IRT when the IRF is imperfectly…
Descriptors: Simulation, Item Response Theory, Monte Carlo Methods, Comparative Analysis
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Brunner, Regina Baron – Mathematics Teacher, 1997
Presents a Monte Carlo simulation on probability using a telephone directory as a pseudorandom-number generator. Claims that Monte Carlo simulations offer a way to teach probability concretely and with understanding and that students enjoy the probability experiments. (ASK)
Descriptors: Class Activities, Mathematics Instruction, Monte Carlo Methods, Probability
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Simon, Julian L.; And Others – American Mathematical Monthly, 1976
The Monte Carlo method and its logic are reviewed, then three experiments that tested the value of the method in a variety of class settings are described. (DT)
Descriptors: College Mathematics, Higher Education, Instruction, Learning Activities
Lowry, Pat G. – Creative Computing, 1981
A program designed to calculate pi using a Monte Carlo simulation based on "throwing darts" at a quarter circle of unit radius inscribed in a unit square is presented. (MP)
Descriptors: Computer Programs, Computer Science Education, Geometric Concepts, Instructional Materials
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Walton, Karen Doyle – Journal of Computers in Mathematics and Science Teaching, 1986
Encourages the use of the microcomputer to teach probability theory and concepts. Presents an instructional sequence and provides 10 activities, three of which have short programs listed. (JM)
Descriptors: Computer Assisted Instruction, Computers, Courseware, Learning Activities
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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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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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Flusser, Peter; Hanna, Dorothy – Mathematics and Computer Education, 1991
Demonstrated is the use of BASIC computer programs to simulate a binomial experiment and test a simple statistical hypothesis. The theoretical results are reached with the third programing attempt. All results, as well as computer programs, are included. (JJK)
Descriptors: College Mathematics, Computer Simulation, Higher Education, Hypothesis Testing
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Houser, Larry L. – Mathematics Teacher, 1981
Monte Carlo methods are used to simulate activities in baseball such as a team's "hot streak" and a hitter's "batting slump." Student participation in such simulations is viewed as a useful method of giving pupils a better understanding of the probability concepts involved. (MP)
Descriptors: Baseball, Mathematical Models, Mathematics Instruction, Models
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Travers, Kenneth J.; Gray, Kenneth G. – Mathematics Teacher, 1981
Some activities designed around the Monte Carlo method of solving probability problems are described. The instructional applications of this method involve physical models or simple BASIC computer programs. (MP)
Descriptors: Computer Programs, Mathematical Applications, Mathematical Models, Mathematics Instruction
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Olson, Donald; And Others – Physics Teacher, 1990
Discusses making a computer-simulated rainbow using principles of physics, such as reflection and refraction. Provides BASIC program for the simulation. Appends a program illustrating the effects of dispersion of the colors. (YP)
Descriptors: College Science, Computer Simulation, Computer Uses in Education, Higher Education
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Mathews, John H. – AMATYC Review, 1989
Describes Newton's method to locate roots of an equation using the Newton-Raphson iteration formula. Develops an adaptive method overcoming limitations of the iteration method. Provides the algorithm and computer program of the adaptive Newton-Raphson method. (YP)
Descriptors: Algorithms, College Mathematics, Computation, Equations (Mathematics)
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Gunther, L.; Weaver, D. L. – American Journal of Physics, 1978
A model of Brownian motion is discussed which includes viscosity effects. The model lends itself to Monte Carlo simulation and thus is suitable for an elementary physics laboratory experiment. (BB)
Descriptors: College Science, Higher Education, Laboratory Experiments, Mathematical Models
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Newell, G. J.; MacFarlane, J. D. – Australian Mathematics Teacher, 1985
Presents sports-oriented examples (cricket and football) in which Monte Carlo methods are used on microcomputers to teach probability concepts. Both examples include computer programs (with listings) which utilize the microcomputer's random number generator. Instructional strategies, with further challenges to help students understand the role of…
Descriptors: Computer Simulation, Computer Software, Estimation (Mathematics), Mathematics Education
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Gordon, Sheldon P.; Gordon, Florence S. – AMATYC Review, 1990
Discusses the application of probabilistic ideas, especially Monte Carlo simulation, to calculus. Describes some applications using the Monte Carlo method: Riemann sums; maximizing and minimizing a function; mean value theorems; and testing conjectures. (YP)
Descriptors: Calculus, College Mathematics, Functions (Mathematics), Higher Education
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