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  • Understanding the Least-Squares Regression Line

    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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  • Regression Applet

    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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  • Quote: Fisher on Observation versus Experiment

    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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  • Song: Heteroscedasticity

    Playful song has recurrent mention of the term heteroscedasticity.

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  • Cartoon: Beethoven's unfinished work

    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: ANOVA Man

    Song includes basic vocabulary from ANOVA. May be sung to "Nowhere Man" (John Lennon, Paul McCartney)

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  • SPSS tutorial for Multiple Comparisons

    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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  • Virtual Manipulative: Box Plot

    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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  • Deriving Regression Lines Without Calculus

    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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  • Dataset Example: What Does It Take to Heat a New Room? Estimating Utility Demand in a Home

    This article describes a dataset containing energy use data for single-family homes and monthly weather data in the Boston area over a seven year period. The data can help illustrate concepts like central tendency, dispersion, time series analysis, correlation, simple and multiple regression, and variable transformations. Key Words: measurement; forecasting.

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