Sophisticated simulations using computer graphics can lead to students deducing virtually all conditions of the Central Limit Theorem. Eight graphs illustrate the discussion. (MNS)

This simple method for simulating the Central Limit Theorem with students in a beginning nonmajor statistics class requires students to use dice to simulate drawing samples from a discrete uniform distribution. On a chalkboard, the distribution of sample means is superimposed on a graph of the discrete uniform distribution to provide visual…

This paper presents a summary of action research investigating statistics students' understandings of the sampling distribution of the mean. With four sections of an introductory Statistics in Education course (n=98 students), a computer simulation activity (R. delMas, J. Garfield, and B. Chance, 1999) was implemented and evaluated to show…

Describes the use of computer graphics simulations to enhance student understanding of sampling distributions that arise in introductory statistics. Highlights include the distribution of sample proportions, the distribution of the difference of sample means, the distribution of the difference of sample proportions, and the distribution of sample…

Describes a hands-on demonstration of the concept of the sampling distribution of the mean using M&M's candy. Compares the effectiveness of the candy demonstration with that of a comparable demonstration using a textbook example. Reports that students exposed to the candy example performed better on a subsequent examination. (DSK)

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…

Analysis of a two-way sample of means is considered when corresponding population means are believed a priori to satisfy a partial order restriction. Simulation and the Gibbs sampler are used to summarize posterior distributions, and the posterior distribution is used to predict GPAs of first-year students at University of Iowa. (SLD)