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  • 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 applet allows students to explore three methods for measuring "goodness of fit" of a linear model. Users can manipulate both the data and the regression line to see changes in the square error, the absolute error, and the shortest distance from the data point to the regression line.
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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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  • That's not an experiment you have there, that's an experience. Ronald A. Fisher (1890-1962.) Quoted in "Statistics", third edition, by David Freedman, Robert Pisani, and Roger Purves (Norton, 1998)
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  • Playful song has recurrent mention of the term heteroscedasticity.
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  • A cartoon that can be used in teaching about pie charts. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.
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  • Song includes basic vocabulary from ANOVA. May be sung to "Nowhere Man" (John Lennon, Paul McCartney)
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  • This tutorial exposes students to conducting multiple comparisons in SPSS. This html based tutorial provides extensive screen shots and an example data set. Topics covered in the tutorial include one way ANOVA, preplanned contrasts, Bonferroni, Post Hoc Tukey's HSD, and Scheffe's multiple contrasts.
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  • This is a Java Applet, which allows you to load your personal data and edit data. It provides interval and endpoint values and the option to view as a histogram.
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  • This article describes a method to calculate the least squares line algebraically. First, the author uses a numeric example, which uses calculus, then describes a simpler algebraic method.
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