Describes a dry- lab" experiment for the college freshman laboratory, in which the essential features of Browian motion are given principles, using the Monte Carlo technique. Calculations principles, using the Monte Carlo technique. Calculations are carried out by a computation sheme based on computer language. Bibliography. (LC)

This paper focuses on mixtures of two binomials with one known success parameter. It is shown how moment estimators can be obtained for the remaining unknown parameters of such mixtures, and results are presented from a Monte Carlo study carried out to explore the statistical properties of these estimators. (PN)

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)

Analyzes a simple boom structure and assesses its reliability using elementary engineering mechanics. Demonstrates the power and utility of Monte-Carlo simulation by showing that such a simulation can be implemented more readily with results that compare favorably to the theoretical calculations. (Author/MM)

To demonstrate that some methods used to assess item fit can be applied to assess person fit and vice versa, performance of a chi-squared item-fit statistic was compared with that of a likelihood-based person-fit statistic for examinees and items under Monte Carlo conditions. (SLD)

A Monte Carlo simulation was used to examine pay-performance relationships. Conventional merit systems achieved a better link between pay and performance than bonus systems, because merit systems benefit from consistency of performance over time. Even very substantial errors in measurement of performance have only a modest effect on…

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)

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)

The use of hierarchical models in social science research is discussed, with emphasis on causal inference and consideration of the limitations of hierarchical models. The increased use of Gibbs sampling and other Markov-chain Monte Carlo methods in the application of hierarchical models is recommended. (SLD)

Through Monte Carlo simulation, respective normative and intuitive strategies for covariation assessment and Bayesian inference are compared. Results indicate that better performance in both tasks results from considering alternative hypotheses, although not necessarily using a normative strategy. Conditions under which intuitive strategies may be…

A modification of a test of the equality of nonindependent alpha reliability coefficients is proposed. It avoids the limitation that the product of the number of test parts times the number of subjects be quite large. Monte Carlo studies indicate that this test can be used in comparing interrater reliabilities. (SLD)

A Monte Carlo study investigated the use of four cross-validation indices with confirmatory factor analysis models. Influences of sample size, loading size, and degree of model misspecification were studied. Larger sample sizes and better specified models result in better cross-validation results. (SLD)

This article describes a Monte Carlo study of 2 methods for treating incomplete nonnormal data. Skewed, kurtotic data sets conforming to a single structured model, but varying in sample size, percentage of data missing, and missing-data mechanism, were produced. An asymptotically distribution-free available-case (ADFAC) method and structured-model…

A new test assembly algorithm based on a Monte Carlo random search is presented in this article. A major advantage of the Monte Carlo test assembly over other approaches (integer programming or enumerative heuristics) is that it performs a uniform sampling from the item pool, which provides every feasible item combination (test) with an equal…