Lecture Examples

  • 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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  • 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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  • This tutorial on Simple Linear Regression includes its definition, assumptions, and characteristics as well as related statistics and hypothesis test procedures. One section instructs users to perform simple linear regression in the WINKS software, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.
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  • This tutorial on the One Sample t test includes its definition, assumptions, hypotheses, and results. An example using output from the WINKS software is given, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.
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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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  • This page gives a description of correlation, Pearson's r, Spearman's rho. There are some scatterplots illustrating the different values of r.

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  • Gives a very brief explanation of Spearman' rho and how it differs from Pearson's r.
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