Continuous

  • The larger the degrees of freedom, the closer the t-density is to the normal density. This reflects the fact that the standard deviation s approaches for large sample size n. You can visualize this in the given applet by moving the sliders.
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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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  • 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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  • This site provides case studies which cover subject areas including: analysis of variance, boxplots, confidence intervals, contrast among means, correlated t-test, correlation, histograms, independent groups t-test, regression, repeated measures ANOVA, and t-tests.
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  • Teacher instructions to accompany "Markov vs. Markov" case study found at http://ublib.buffalo.edu/libraries/projects/cases/markov/markov.html.
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  • Generate a graphic and numerical display of the properties of the Normal Distribution. For a unit normal distribution, with M=0 and SD=Œ±1, enter 0 and 1 at the prompt. For a distribution with M=100 and SD=Œ±15, enter 100 and 15. And so forth

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