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  • **Normal Approximation to the Binomial Distribution

    This demonstration allows you to view the binomial distribution and the normal approximation to it as a function of the probability of a success on a given trial and the number of trials. It can be used to compute binomial probabilities and normal approximations of those probabilities.

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  • DAU StatRefresher: Moving Averages

    This tutorial includes using, finding, weighting, and solving problems with Moving Averages.

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  • Components of r

    As described on the page itself: "The simulation shows a scatterplot of data from a bivariate distribution in which the relationship between the two variables is linear. You can change the "input" values of slope, standard error of the estimate, or standard deviation of X for this data sample, and see the effects of your change. "

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  • DAU StatRefresher: Exponential Smoothing

    This interactive tutorial on Exponential Smoothing helps learners understand the use of exponential smoothing, define exponential smoothing, cite the merits and demerits of exponential smoothing, and solve exercise problems using exponential smoothing.

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  • Data+Applet : Regression by Eye

    In this demonstration a scatterplot is displayed and you draw in a regression line by hand. You can then compare your line to the best least squares fit. You can also try to guess the value of Pearson's correlation coefficient.

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  • DAU StatRefresher: Clustering Algorithms

    This interactive module helps students to understand the definition of and uses for clustering algorithms. Students will learn to categorize the types of clustering algorithms, to use the minimal spanning tree and the k-means clustering algorithm, and to solve exercise problems using clustering algorithms.

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  • Data+Applet: Restriction of Range

    This applet shows how the correlation between two variables is affected by the range of the variable plotted on the X-axis.

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  • DAU StatRefresher: Final Test

    This module is a short quiz which gives a review/assessment of the main concepts for this refresher course. At the bottom, there is a grading button to rate the understanding of the material.

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  • A "Small" Effect Size Can Make a Large Difference

    This applet demonstrates that even a "small" effect can be important under some circumstances. Applicants from two groups apply for a job. The user manipulates the mean and the cut-off score in order to see the effects the small changes has on the number of people hired in each group. The effects on the proportion of hired applicants from each group are displayed.(Requires a browser that supports Java).

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  • Data Summary Project

    The goal of this assignment is to obtain summary statistics for the variables in the data set, ncbirth1450.xls, which represents a random sample of 1450 births from the state of North Carolina.

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