The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data…

Grading on the curve is a common practice in higher education. While there are many critics of the practice it still finds wide spread acceptance particularly in science classes. Advocates believe that in large classes student ability is likely to be normally distributed. If test scores are also normally distributed instructors and students tend…

Classroom demonstrations can help students gain insights into statistical concepts and phenomena. After discussing four kinds of demonstrations, the authors present three possible approaches for determining how much data are needed for the demonstration to have a reasonable probability for success. (Author/LMO)

Describes how microcomputers can perform very demanding/large-scale physics calculations at speeds not much slower than those of modern, full-size computers. Among the examples provided are a Monte Carlo simulation of the three-dimensional Ising model and a program (for the Apple microcomputer) using the time-independent Schrodinger Equation. (JN)

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)

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)

Monte Carlo simulation is a computer modeling procedure for mimicking observations on a random variable. A random number generator is used in generating the outcome for the events that are being modeled. The simulation can be used to obtain results that otherwise require extensive testing or complicated computations. This paper describes how Monte…

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)

A normally distributed data set of 1,000 values--ranging from 50 to 150, with a mean of 50 and a standard deviation of 20--was created in order to evaluate the bootstrap method of repeated random sampling. Nine bootstrap samples of N=10 and nine more bootstrap samples of N=25 were randomly selected. One thousand random samples were selected from…

This article describes a monte carlo computer simulation of affirmative action employment policies. The counterintuitive results of the model are explained through a thought device involving urns and marbles. States that such model simulations have implications for social policy. (BSR)

This paper describes DATASIM, a comprehensive software package which generates simulated data for actual or hypothetical research designs. DATASIM is primarily intended for use in statistics and research methods courses, where it is used to generate "individualized" datasets for students to analyze, and later to correct their answers.…

Discussion of the use of computer simulation in the social sciences highlights types of simulation strategies and their combinations in comprehensive simulations. The strengths and weaknesses of simulations as instructional and research tools are examined, examples are given, and design issues arising in each type are explored. (29 references)…

Two sets of real sorting data from 50 college students are used to compare results of multidimensional scaling of raw co-occurrence frequencies or dissimilarity measures (D) and profile distances (delta) to determine which yields a better representation of the underlying structure of 2 sets of stimuli. Slight differences are discussed. (SLD)

An experimental class in introductory statistics (n=40) using simulation software at American University was compared to a traditionally taught control group (n=36) with respect to achievement and accrued beliefs about the benefits of the simulations. Results indicate significantly higher achievement scores for the experimental class with about…

Describes the deterministic simulation (a given input always leads to the same output) and probabilistic simulation (new states are subject to predefined laws of chance). Provides examples of the application of the two simulations with mathematical expressions and PASCAL program. Lists seven references. (YP)