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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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  • An online Introduction to Biostatistics course complete with lecture notes and links for futher reading, links to applets, and exercises with solutions given.
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  • 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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  • A series of pamphlets place online by the American Statistical Association, Survey Research Methods Section. Each pamphlet deals with a different aspect of survey research and how it is done.
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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 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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  • 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 case study explores statistics on divorce rates using Markov chains. Two closely related statistics are presented: the chance of divorcing in a given year and the chance of divorcing over the lifetime of a marriage. Accompanying teacher instructions are found at http://ublib.buffalo.edu/libraries/projects/cases/markov/markov_notes.html
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