Probability

  • This article addresses the reporting of meta-analyses of observational studies in order to aid authors, reviewers, editors and readers when reading or writing such reports.
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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 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 explains small sample hypothesis testing for a normal population and hypothesis testing for a population proportion. Includes examples and exercises.
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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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  • This chapter of the "Concepts and Applications of Inferential Statistics" online textbook describes in detail the Kruskal-Wallis test, it's formulas, variables, and procedures using an example involving wine-tasters.

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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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  • By changing the number of degrees of freedom in a t-distribution, students can see how the pdf changes. They also have the option of overlayng the standard normal curve so that they can see the convergence.
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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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