Java Applet

  • This page provides a table for selecting an appropriate statistical method based on type of data and what information is desired from the data. It also compares parametric and nonparametric tests, one-sided and two-sided p-values, paired and unpaired tests, Fisher's test and the Chi-square test, and regression and correlation. It comes from Chapter 37 of the textbook, "Intuitive Biostatistics".
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  • This module discusses the probability of an event and relative frequency. The applet shows how empirical probability converges to theoretical probability as the sample size increases. The follow-up example includes an applet that simulates drawing differently colored balls from an urn.
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  • This collection of datasets comes from several phases of drug research. Each dataset comes with a full description and questions to answer from the data.
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  • This applet was designed to illustrate the impact on simple linear regression output caused by adding a new data point. The applet simulates data and provides a graphical display of the data points and fitted regression line as well as the updated regression line after the addition of a data point.
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  • This JAVA applet assists the user in developing skills to classify a problem as one of the various types of confidence intervals, hypethesis tests and Chi Squared tests. This is not an easy application, but the comprehensive hints provided will improve the users skills in making such classifications.
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  • This applet displays various distributions and allows the user to experiment with the parameters to see the effects on the curve.

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  • Submitting your spotlight presentation from USCOTS 2005 to CAUSEweb is an easy process, and you are in a prime position to submit your work! What better way to have your work showcased than in a peer-reviewed repository of contributions to statistics education? This Webinar from January 2006 provided an opportunity to talk about how to prepare your USCOTS spotlight for submission to CAUSEweb and to discuss the benefits of submission.

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  • This Flash based applet simulates data from a case study of treatments for tumor growth in mice. This simulation allows the user to place mice into a control and treatment groups. The simulation then compares the difference in the groups based on this haphazard selection to those of a truly random assignment (the user may also create multiple random assignments and examine the sampling distribution of key statistics). The applet may be used to illustrate three points about random assignment in experiments: 1) how it helps to eliminate bias when compared with a haphazard assignment process, 2) how it leads to a consistent pattern of results when repeated, and 3) how it makes the question of statistical significance interesting since differences between groups are either from treatment or by the luck of the draw. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and assessments. Key Note for Instructors: The data are drawn from a real experiment with an effective treatment but where the response is correlated with animal age and size (so tumor size will tend to be smaller in the treatment group when measured at the end of a randomized experiment but animal age and size should not be). Typically people choosing haphazardly will tend to pick larger/older animals for the treatment group and thus create a bias against the treatment.
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  • It is now proved beyond doubt that smoking is one of the leading causes of statistics. Quote found in "Reader's Digest" (December, 1961) by journalist Fletcher Knebel (1911-1993)
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  • Joke from "The Little Black Book of Business Statistics", by Michael C. Thomsett (1990, Amacom) p. 117. also quoted in "Statistically Speaking" compiled by Carl Gaither and Alma Cavazos-Gaither.
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