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  • This page introduces contigency tables with an example on fruit trees and fire blight. Two calculators are provided that allow users to enter their own contigency table and test for treatment effects. The first calculator performs Fisher's Exact Test on a 2x2 tables. The second performs a chi-square test on up to a 9x9 table.

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  • This page introduces the Kolmogorov-Smirnov test, gives background and procedures for the test, and provides a calculation page which allows users to enter their own data and perform the test.

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  • Compared to probability calculators, the traditional format of distribution tables has the advantage of showing many values simultaneously and, thus, enables the user to examine and quickly explore ranges of probabilities. This webpage includes a list of distributions and tables, including the standard normal (Z) table, student's t table, chi-square table, and F distribution tables. An animation of the density function and distribution function is shown above each distribution table to demonstrate the effects changing degrees of freedom and significance levels have on the shape of a distribution.

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  • March 24, 2009 Activity webinar presented by Nicholas Horton, Smith College, and hosted by Leigh Slauson, Otterbein College. Students have a hard time making the connection between variance and risk. To convey the connection, Foster and Stine (Being Warren Buffett: A Classroom Simulation of Risk and Wealth when Investing in the Stock Market; The American Statistician, 2006, 60:53-60) developed a classroom simulation. In the simulation, groups of students roll three colored dice that determine the success of three "investments". The simulated investments behave quite differently. The value of one remains almost constant, another drifts slowly upward, and the third climbs to extremes or plummets. As the simulation proceeds, some groups have great success with this last investment--they become the "Warren Buffetts" of the class. For most groups, however, this last investment leads to ruin because of variance in its returns. The marked difference in outcomes shows students how hard it is to separate luck from skill. The simulation also demonstrates how portfolios, weighted combinations of investments, reduce the variance. In the simulation, a mixture of two poor investments is surprisingly good. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and references (extra materials available for download free of charge)

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  • When performing a hypothesis test about the population mean, a possible reason for the failure of rejection of the null hypothesis is that there's an insufficient sample size to achieve a powerful test. Using a small data set, Minitab is used to check for normality of the data, to perform a 1-Sample t test, and to compute Power and Sample Size for 1-Sample t.

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  • This site is a description of the mathematics behind survival analysis. It starts with a definition of the survival function. Then it discusses estimating the survival function with the Kaplan-Meier curve.  Then it discusses comparing survival curves. Finally, there is a discussion of Cox Proportional Hazards regression analysis.

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  • This site is a government-run repository of information on current and completed clinical trials. Users can search for clinical trials by disease type and also by whether the trial is currently recruiting. Then a detailed description of the trial is given. This can be used in a classroom setting to discuss design issues and ethical issues with clinical trials.

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  • This website is a summary of a randomized controlled trial of a metropolitan police department's body-worn camera program. It is useful in class to talk about the design of the experiment and also to talk about how they state their results. Their results are given as confidence intervals for differences.

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  • Song incorporates various terms from areas such as experimental design, graphing, and hypothesis testing. May be sung to the tune of "Desperado" (The Eagles). Musical accompaniment realization are by Joshua Lintz and vocals are by Mariana Sandoval from University of Texas at El Paso.

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  • This is a complete lesson module (including example problems with answers to selected problems) for the purpose of enabling students to: 1) Provide examples demonstrating how the margin of error, effect size, and variability of the outcome affect sample size computations. 2) Compute the sample size required to estimate population parameters with precision. 3) Interpret statistical power in tests of hypothesis. 4) Compute the sample size required to ensure high power when hypothesis testing.
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