Resource Library

This page of Statistical Java describes 11 different probability distributions including the Binomial, Poisson, Negative Binomial, Geometric, T, Chi-squared, Gamma, Weibull, Log-Normal, Beta, and F. Each distribution has its own applet in which users can manipulate the parameters to see how the distribution changes. The parameters are described on the main page as well as situations that would use each distribution. The equations of the distributions are not given. To select between the different applets you can click on Statistical Theory, Probability Distributions and then the Main Page. At the bottom of this page you can make your applet selection. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/

This collection of Analysis Tools can assist students and researchers with questions about study desgin, data analysis, and probability. Topics include sample size, power, survival, binomial probabilities, interaction, Fisher's exact test, one and two sample tests, and more.

This online, interactive lesson on hypothesis testing provides examples, exercises, and applets which includes tests in the normal model, Bernoulli Model, and two-sample normal model as well as likelihood ratio and goodness of fit tests.

This random number service allows users to generate up to 10,000 random integers with duplicates, randomized sequences without duplicates, or up to 16 kilobytes of raw random bytes. Users can also flip virtual coins and generate random bitmaps. Key word: Random Number Generator.

This calculator computes the chi-square statistic, degrees of freedom (DoF), and p-value for the Chi-square test for equality of distributions. Users input a table of values with row and column labels without total scores. The null hypothesis is that the all the samples have the same distribution.

This test checks whether an observed distribution differs from an expected distribution. It computes the chi-square statistic, degrees of freedom (DoF), and p-value. Users input a table with row and column labels, observed frequencies on the first row, and expected frequencies on the second row. The null hypothesis is that the observed values have the expected frequency distribution.