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  • This JAVA applet is designed to give students practice in calculating basic probabilities using the binomial distribution. The applet gives students short problem descriptions that require a binomial probability to solve. The user is then prompted to follow a step by step process to find the probability. Users must answer a step correctly before the applet will allow them to move on to the next step. The page also gives further exercises that allow the user to think about binomial distributions more deeply and gives a link to a more detailed information about the binomial distribution.
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  • This page discusses the procedures and applications of the two sample t test and the paired t test.
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  • The seventh chapter of an online Introduction to Biostatistics course. Two sets of lecture notes are provided (only the first one works). Additionally, links for additional reading and exercises with solutions are provided.
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  • This section on Common Statistical Tests uses an example on faculty publications to show users how to perform a one-sample t test. The discussion includes one-tailed and two-tailed tests.
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  • This site focuses on using the LRT to compare two competing models.
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  • This site offers an involved definition of the likelihood ratio test with examples and formulas.
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  • Explains how to set up the Kruskal-Wallis test and gives the formula for the test statistic.
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  • This applet allows the user to adjust a (1st shape) and b (2nd shape) parmaters of the Beta distribution with a slider or manual input. The applet allows the user to fix the x and or y axes. The user immediately sees how this affects the the shape of the graph as well as the variance and the expected value. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/BetaDensityApplet.html
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  • The eighth chapter of an online Introduction to Biostatistics course. Lecture notes are provided. Additionally, links for additional reading and exercises with solutions are provided.
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  • Gives a very brief explanation of Spearman' rho and how it differs from Pearson's r.
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